- IJCAI-2023 ICML-2023 KDD-2023 SIGIR-2023 NeurIPS-2023 CIKM-2023 AAAI-2023 ICLR-2023 WSDM-2023 WWW-2023 ICDE-2023 SIGMOD-2023
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Self-supervised Graph Disentangled Networks for Review-based Recommendation
Yuyang Ren, Haonan Zhang, Qi Li, Luoyi Fu, Xinbing Wang, Chenghu Zhou
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A Canonicalization-Enhanced Known Fact-Aware Framework For Open Knowledge Graph Link Prediction
Yilin Wang, Minghao Hu, Zhen Huang, Dongsheng Li, Wei Luo, Dong Yang, Xicheng Lu
-
KDLGT: A Linear Graph Transformer Framework via Kernel Decomposition Approach
Yi Wu, Yanyang Xu, Wenhao Zhu, Guojie Song, Zhouchen Lin, Liang Wang, Shaoguo Liu
-
Multi-level Graph Contrastive Prototypical Clustering
Yuchao Zhang, Yuan Yuan, Qi Wang
-
Graph Propagation Transformer for Graph Representation Learning
Zhe Chen, Hao Tan, Tao Wang, Tianrun Shen, Tong Lu, Qiuying Peng, Cheng Cheng, Yue Qi
-
Graph Sampling-based Meta-Learning for Molecular Property Prediction
Xiang Zhuang, Qiang Zhang, Bin Wu, Keyan Ding, Yin Fang, Huajun Chen
-
A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks
Mehrdad khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K Reddy
-
PPAT: Progressive Graph Pairwise Attention Network for Event Causality Identification
Zhenyu Liu, Baotian Hu, Zhenran Xu, Min Zhang
-
Violin: Virtual Overbridge Linking for Enhancing Semi-supervised Learning on Graphs with Limited Labels
Siyue Xie, Da Sun Handason Tam, Wing Cheong Lau
-
Hierarchical Transformer for Scalable Graph Learning
Wenhao Zhu, Tianyu Wen, Guojie Song, Xiaojun Ma, Liang Wang
-
Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation
Yalin Yu, Enneng Yang, Guibing Guo, Linying Jiang, Xingwei Wang
-
Totally Dynamic Hypergraph Neural Networks
Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu
-
Gapformer: Graph Transformer with Graph Pooling for Node Classification
Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu
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One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction
Jan Tönshoff, Berke Kisin, Jakob Lindner, Martin Grohe
-
Continuous-Time Graph Learning for Cascade Popularity Prediction
Xiaodong Lu, Shuo Ji, Le Yu, Leilei Sun, Bowen Du, Tongyu Zhu
-
CSGCL: Community-Strength-Enhanced Graph Contrastive Learning
Han Chen, Ziwen Zhao, Yuhua Li, Yixiong Zou, Ruixuan Li, Rui Zhang
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Enabling Abductive Learning to Exploit Knowledge Graph
Yu-Xuan Huang, Zequn Sun, Guangyao Li, Xiaobin Tian, Wang-Zhou Dai, Wei Hu, Yuan Jiang, Zhi-Hua Zhou
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CONGREGATE: Contrastive Graph Clustering in Curvature Spaces
Li Sun, Feiyang Wang, Junda Ye, Hao Peng, Philip S. Yu
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LGI-GT: Graph Transformers with Local and Global Operators Interleaving
Shuo Yin, Guoqiang Zhong
-
An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural Representations
Achille Fokoue, Ibrahim Abdelaziz, Maxwell Crouse, Shajith Ikbal, Akihiro Kishimoto, Guilherme Lima, Ndivhuwo Makondo, Radu Marinescu
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MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation
Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
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LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity
Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao
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Globally Consistent Federated Graph Autoencoder for Non-IID Graphs
Kun Guo, Yutong Fang, Qingqing Huang, Yuting Liang, Ziyao Zhang, Wenyu He, Liu Yang, Kai Chen, Ximeng Liu, Wenzhong Guo
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SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein–Protein Interaction Prediction
Ziyuan Zhao, Peisheng Qian, Xulei Yang, Zeng Zeng, Cuntai Guan, Wai Leong Tam, Xiaoli Li
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Minimizing Reachability Times on Temporal Graphs via Shifting Labels
Argyrios Deligkas, Eduard Eiben, George Skretas
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Beyond Homophily: Robust Graph Anomaly Detection via Neural Sparsification
Zheng Gong, Guifeng Wang, Ying Sun, Qi Liu, Yuting Ning, Hui Xiong, Jingyu Peng
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SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs
Sheng Tian, Jihai Dong, Jintang Li, WENLONG ZHAO, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen
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Graph Neural Convection-Diffusion with Heterophily
KAI ZHAO, Qiyu Kang, Yang Song, Rui She, Sijie Wang, Wee Peng Tay
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Semi-supervised Domain Adaptation in Graph Transfer Learning
Ziyue Qiao, Xiao Luo, Meng Xiao, Hao Dong, Yuanchun Zhou, Hui Xiong
-
Multi-Scale Subgraph Contrastive Learning
Yanbei Liu, Yu Zhao, Xiao Wang, Lei Geng, Zhitao Xiao
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Multi-view Contrastive Learning Hypergraph Neural Network for Drug-Microbe-Disease Association Prediction
Luotao Liu, Feng Huang, Xuan Liu, Zhankun Xiong, Menglu Li, Congzhi Song, Wen Zhang
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Multi-View Robust Graph Representation Learning for Graph Classification
Guanghui Ma, Chunming Hu, Ling Ge, Hong Zhang
-
Graph-based Semi-supervised Local Clustering with Few Labeled Nodes
Zhaiming Shen, Ming-Jun Lai, Sheng Li
-
Adaptive Path-Memory Network for Temporal Knowledge Graph Reasoning
Hao Dong, Zhiyuan Ning, Pengyang Wang, Ziyue Qiao, Pengfei Wang, Yuanchun Zhou, Yanjie Fu
-
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks
Xinyu Fu, Irwin King
-
Intent-aware Recommendation via Disentangled Graph Contrastive Learning
Yuling Wang, Xiao Wang, Xiangzhou Huang, Yanhua Yu, Haoyang Li, Mengdi Zhang, Zirui Guo, Wei Wu
-
Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction
Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King
-
Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention
Hongjun Wang, Jiyuan Chen, Lun Du, Qiang Fu, Shi Han, Xuan Song
-
A Generalization of ViT/MLP-Mixer to Graphs
Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson
-
A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
Yifan Chen, Rentian Yao, Yun Yang, Jie Chen
-
Additive Causal Bandits with Unknown Graph
Alan Malek, Virginia Aglietti, Silvia Chiappa
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Alternately Optimized Graph Neural Networks
Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang
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Boosting Graph Contrastive Learning via Graph Contrastive Saliency
Chunyu Wei, Yu Wang, Bing Bai, Kai Ni, David J. Brady, LU FANG
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ClusterFuG: Clustering Fully connected Graphs by Multicut
Ahmed Abbas, Paul Swoboda
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CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification
Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian-Sheng Hua, Xiao Luo
-
Conditional Graph Information Bottleneck for Molecular Relational Learning
Namkyeong Lee, Dongmin Hyun, Gyoung S. Na, Sungwon Kim, Junseok Lee, Chanyoung Park
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D2Match: Leveraging Deep Learning and Degeneracy for Subgraph Matching
Xuanzhou Liu, Lin Zhang, Jiaqi Sun, Yujiu Yang, Haiqin Yang
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DRew: Dynamically Rewired Message Passing with Delay
Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
-
Dink-Net: Neural Clustering on Large Graphs
Yue Liu, KE LIANG, Jun Xia, sihang zhou, Xihong Yang, Xinwang Liu, Stan Z. Li
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Disentangled Multiplex Graph Representation Learning
Yujie Mo, Yajie Lei, Jialie Shen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu
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Distribution Free Prediction Sets for Node Classification
Jase Clarkson
-
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks
Peng XU, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqin Yang, Bei Yu
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ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines
Siyuan Chen, Pratik Pramod Fegade, Tianqi Chen, Phillip Gibbons, Todd Mowry
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Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation
Joonhyuk Yang, Dongpil Shin, Hye Won Chung
-
Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network
Yadi Cao, Menglei Chai, Minchen Li, Chenfanfu Jiang
-
Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling
Xiaohui Chen, Jiaxing He, Xu Han, Liping Liu
-
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian
Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
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Ewald-based Long-Range Message Passing for Molecular Graphs
Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann
-
Exphormer: Sparse Transformers for Graphs
Hamed Shirzad, Ameya Velingker, Balaji Venkatachalam, Danica J. Sutherland, Ali Kemal Sinop
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Fast Online Node Labeling for Very Large Graphs
Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh
-
Featured Graph Coarsening with Similarity Guarantees
Manoj Kumar, Anurag Sharma, Shashwat Saxena, Sandeep Kumar
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Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs
YIZHEN ZHENG, He Zhang, Vincent Lee, Yu Zheng, Xiao Wang, Shirui Pan
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Fisher Information Embedding for Node and Graph Learning
Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt
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From Hypergraph Energy Functions to Hypergraph Neural Networks
Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf
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From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks
Cai Zhou, Xiyuan Wang, Muhan Zhang
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GC-Flow: A Graph-Based Flow Network for Effective Clustering
Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen
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GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming
Huigen Ye, Hua Xu, Hongyan Wang, Chengming Wang, Yu Jiang
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GREAD: Graph Neural Reaction-Diffusion Networks
Jeongwhan Choi, Seoyoung Hong, Noseong Park, Sung-Bae Cho
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Generated Graph Detection
Yihan Ma, Zhikun Zhang, Ning Yu, Xinlei He, Michael Backes, Yun Shen, Yang Zhang
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Graph Contrastive Backdoor Attacks
Hangfan Zhang, Jinghui Chen, Lu Lin, Jinyuan Jia, Dinghao Wu
-
Graph Generative Model for Benchmarking Graph Neural Networks
Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov
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Graph Inductive Biases in Transformers without Message Passing
Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip Torr, Ser-Nam Lim
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Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication
AJAY KUMAR JAISWAL, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
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Graph Mixup with Soft Alignments
Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou
-
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure
Ryoma Sato
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Graph Neural Networks with Learnable and Optimal Polynomial Bases
Yuhe Guo, Zhewei Wei
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Graph Neural Tangent Kernel: Convergence on Large Graphs
Sanjukta Krishnagopal, Luana Ruiz
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Graph Positional Encoding via Random Feature Propagation
Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
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GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks
Yuwen Li, Miao Xiong, Bryan Hooi
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HOPE: High-order Graph ODE For Modeling Interacting Dynamics
Xiao Luo, Jingyang Yuan, Zijie Huang, Huiyu Jiang, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun
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Half-Hop: A graph upsampling approach for slowing down message passing
Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Veličković, Eva L Dyer
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Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction
Minghao Guo, Veronika Thost, Samuel W Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik
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Implicit Graph Neural Networks: A Monotone Operator Viewpoint
Justin Baker, Qingsong Wang, Cory D Hauck, Bao Wang
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Improving Graph Generation by Restricting Graph Bandwidth
Nathaniel Lee Diamant, Alex Tseng, Kangway V Chuang, Tommaso Biancalani, Gabriele Scalia
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Improving Graph Neural Networks with Learnable Propagation Operators
Moshe Eliasof, Lars Ruthotto, Eran Treister
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InGram: Inductive Knowledge Graph Embedding via Relation Graphs
Jaejun Lee, Chanyoung Chung, Joyce Jiyoung Whang
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LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu
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Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs
Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco
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Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks
Feng Ji, See Hian Lee, Hanyang Meng, Kai Zhao, Jielong Yang, Wee Peng Tay
-
Linkless Link Prediction via Relational Distillation
Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh Chawla, Neil Shah, Tong Zhao
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Local Vertex Colouring Graph Neural Networks
Shouheng Li, Dongwoo Kim, Qing Wang
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Modeling Dynamic Environments with Scene Graph Memory
Andrey Kurenkov, Michael Lingelbach, Tanmay Agarwal, Emily Jin, Chengshu Li, Ruohan Zhang, Li Fei-Fei, Jiajun Wu, Silvio Savarese, Roberto Martín-Martín
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Multi-class Graph Clustering via Approximated Effective
$p$ -ResistanceShota Saito, Mark Herbster
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Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks
Qiyu Kang, Kai Zhao, Yang Song, Sijie Wang, Wee Peng Tay
-
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs
Richard A Watson, Hengrui Cai, Xinming An, Samuel McLean, Rui Song
-
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein
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On the Connection Between MPNN and Graph Transformer
Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang
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On the Expressive Power of Geometric Graph Neural Networks
Chaitanya K. Joshi, Cristian Bodnar, Simon V Mathis, Taco Cohen, Pietro Lio
-
One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding
Daniel Severo, James Townsend, Ashish J Khisti, Alireza Makhzani
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Online Learning with Feedback Graphs: The True Shape of Regret
Tomáš Kocák, Alexandra Carpentier
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PLay: Parametrically Conditioned Layout Generation using Latent Diffusion
Chin-Yi Cheng, Forrest Huang, Gang Li, Yang Li
-
Path Neural Networks: Expressive and Accurate Graph Neural Networks
Gaspard Michel, Giannis Nikolentzos, Johannes F. Lutzeyer, Michalis Vazirgiannis
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Personalized Subgraph Federated Learning
Jinheon Baek, Wonyong Jeong, Jiongdao Jin, Jaehong Yoon, Sung Ju Hwang
-
Randomized Schur Complement Views for Graph Contrastive Learning
Vignesh Kothapalli
-
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs
Saro Passaro, C. Lawrence Zitnick
-
Relevant Walk Search for Explaining Graph Neural Networks
Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus Robert Muller, Shinichi Nakajima
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Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching
Fang Wu, Siyuan Li, Xurui Jin, Yinghui Jiang, Dragomir Radev, Zhangming Niu, Stan Z. Li
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Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
Khang Nguyen, Nong Minh Hieu, Vinh Duc NGUYEN, Nhat Ho, Stanley Osher, Tan Minh Nguyen
-
Rotation and Translation Invariant Representation Learning with Implicit Neural Representations
Sehyun Kwon, Joo Young Choi, Ernest K. Ryu
-
SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning
Junran Wu, Xueyuan Chen, Bowen Shi, Shangzhe Li, Ke Xu
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Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
-
SlotGAT: Slot-based Message Passing for Heterogeneous Graphs
Ziang Zhou, Jieming Shi, Renchi Yang, Yuanhang Zou, Qing Li
-
Theoretical Bounds on the Network Community Profile from Low-rank Semi-definite Programming
Yufan Huang, C. Seshadhri, David F. Gleich
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Tight and fast generalization error bound of graph embedding in metric space
Atsushi Suzuki, Atsushi Nitanda, Taiji Suzuki, jing wang, Feng Tian, Kenji Yamanishi
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Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering
Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi
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Towards Deep Attention in Graph Neural Networks: Problems and Remedies
Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin
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Towards Robust Graph Incremental Learning on Evolving Graphs
Junwei Su, Difan Zou, Zijun Zhang, Chuan Wu
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Towards Understanding and Reducing Graph Structural Noise for GNNs
Mingze Dong, Yuval Kluger
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Transformers Meet Directed Graphs
Simon Geisler, Yujia Li, Daniel J Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru
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Understanding Oversquashing in GNNs through the Lens of Effective Resistance
Mitchell Black, Zhengchao Wan, Amir Nayyeri, Yusu Wang
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Vertical Federated Graph Neural Network for Recommender System
Peihua Mai, Yan Pang
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WL meet VC
Christopher Morris, Floris Geerts, Jan Tönshoff, Martin Grohe
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Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks
Xu Chu, Yujie Jin, Xin Wang, Shanghang Zhang, Yasha Wang, Wenwu Zhu, Hong Mei
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Which Invariance Should We Transfer? A Causal Minimax Learning Approach
Mingzhou Liu, Xiangyu Zheng, Xinwei Sun, Fang Fang, Yizhou Wang
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Kernel Ridge Regression-Based Graph Dataset Distillation
Zhe Xu, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hao Yang, Hanghang Tong
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Reducing Exposure to Harmful Content via Graph Rewiring
Corinna Coupette, Stefan Neumann, Aristides Gionis
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Community-based Dynamic Graph Learning for Popularity Prediction
Shuo Ji, Xiaodong Lu, Mingzhe Liu, Leilei Sun, Chuanren Liu, Bowen Du, Hui Xiong
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GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network
Ran Jia, Haoming Guo, Xiaoyuan Jin, Chao Yan, Lun Du, Xiaojun Ma, Tamara Stankovic, Marko Lozajic, Goran Zoranovic, Igor Ilic, Shi Han, Dongmei Zhang
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Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective
Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng
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MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
Jiaxing Zhang, Dongsheng Luo, Hua Wei
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Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-Scale Disentangled Representations
Haoyu Geng, Chao Chen, Yixuan He, Gang Zeng, Zhaobing Han, Hua Chai, Junchi Yan
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What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang
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Efficient and Effective Edge-Wise Graph Representation Learning
Hewen Wang, Renchi Yang, Keke Huang, Xiaokui Xiao
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Towards Graph-Level Anomaly Detection via Deep Evolutionary Mapping
Xiaoxiao Ma, Jia Wu, Jian Yang, Quan Z. Sheng
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VQNE: Variational Quantum Network Embedding with Application to Network Alignment
Xinyu Ye, Ge Yan, Junchi Yan
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CARL-G: Clustering-Accelerated Representation Learning on Graphs
William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis
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On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms
Fanchen Bu, Kijung Shin
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Densest Diverse Subgraphs: How to Plan a Successful Cocktail Party with Diversity
Atsushi Miyauchi, Tianyi Chen, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
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Localised Adaptive Spatial-Temporal Graph Neural Network
Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao
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PERT-GNN: Latency Prediction for Microservice-Based Cloud-Native Applications via Graph Neural Networks
Da Sun Handason Tam, Yang Liu, Huanle Xu, Siyue Xie, Wing Cheong Lau
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Causal Effect Estimation on Hierarchical Spatial Graph Data
Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi
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Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information
Tianjun Yao, Yingxu Wang, Kun Zhang, Shangsong Liang
-
On Structural Expressive Power of Graph Transformers
Wenhao Zhu, Tianyu Wen, Guojie Song, Liang Wang, Bo Zheng
-
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem
Guanyu Cui, Zhewei Wei
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Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization
Kaixuan Chen, Shunyu Liu, Tongtian Zhu, Ji Qiao, Yun Su, Yingjie Tian, Tongya Zheng, Haofei Zhang, Zunlei Feng, Jingwen Ye, Mingli Song
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Learning Strong Graph Neural Networks with Weak Information
Yixin Liu, Kaize Ding, Jianling Wang, Vincent Lee, Huan Liu, Shirui Pan
-
Clenshaw Graph Neural Networks
Yuhe Guo, Zhewei Wei
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All in One: Multi-Task Prompting for Graph Neural Networks
Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan
-
Certified Edge Unlearning for Graph Neural Networks
Kun Wu, Jie Shen, Yue Ning, Ting Wang, Wendy Hui Wang
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Augmenting Recurrent Graph Neural Networks with a Cache
Guixiang Ma, Vy A Vo, Theodore L. Willke, Nesreen K. Ahmed
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Narrow the Input Mismatch in Deep Graph Neural Network Distillation
Qiqi Zhou, Yanyan Shen, Lei Chen
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Sketch-Based Anomaly Detection in Streaming Graphs
Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip Yu, Bryan Hooi
-
Knowledge Graph Reasoning over Entities and Numerical Values
Jiaxin Bai, Chen Luo, zheng li, Qingyu Yin, Bing Yin, Yangqiu Song
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Exploiting Relation-Aware Attribute Representation Learning in Knowledge Graph Embedding for Numerical Reasoning
Gayeong Kim, Sookyung Kim, Ko Keun Kim, Suchan Park, Heesoo Jung, Hogun Park
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AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning
Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han
-
Context-Aware Event Forecasting via Graph Disentanglement
Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-seng Chua
-
Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers
Chanyoung Chung, Jaejun Lee, Joyce Jiyoung Whang
-
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks
Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan
-
Grace: Graph Self-Distillation and Completion to Mitigate Degree-Relatednesses
Hui Xu, Liyao Xiang, Femke Huang, Yuting Weng, Ruijie Xu, Xinbing Wang, Chenghu Zhou
-
GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification
Wen-Zhi Li, Chang-Dong Wang, Hui Xiong; The Hong Kong University of Science and Technology), Jian-Huang Lai
-
Classification of Edge-Dependent Labels of Nodes in Hypergraphs
Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin
-
Enhancing Graph Representations Learning with Decorrelated Propagation
Hua Liu, Wei Jin, Xiaorui Liu, Hui Liu
-
Meta Graph Learning for Long-Tail Recommendation
Chunyu Wei, Jian Liang, Di Liu, Zehui Dai, Mang Li, Fei Wang
-
Graph Neural Bandits
Yunzhe Qi, Yikun Ban, Jingrui He
-
E-commerce Search via Content Collaborative Graph Neural Network
Guipeng Xv, Chen Lin, Wanxian Guan, Jinping Gou, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng
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Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation
Jin-Duk Park, Siqing Li, Xin Cao, Won-Yong Shin
-
Knowledge Graph Self-Supervised Rationalization for Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang
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On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering
Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang
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Incremental Causal Graph Learning for Online Root Cause Analysis
Dongjie Wang, Zhengzhang Chen, Yanjie Fu, Yanchi Liu, Haifeng Chen
-
Transferable Graph Structure Learning for Graph-Based Traffic Forecasting Across Cities
Yilun Jin, Kai Chen, Qiang Yang
-
FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework
Raneen Younis, Zahra Ahmadi, Abdul Hakmeh, Marco Fisichella
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Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-Source Knowledge Graphs
Zequn Sun, Jiacheng Huang, Jinghao Lin, Xiaozhou Xu, Qijin Chen, Wei Hu
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Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation
Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen
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Few-Shot Low-Resource Knowledge Graph Completion with Multi-view Task Representation Generation
Shichao Pei, Ziyi Kou, Qiannan Zhang, Xiangliang Zhang
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Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree
Delvin Ce Zhang, Rex Ying, Hady W. Lauw
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PROSE: Graph Structure Learning via Progressive Strategy
Huizhao Wang, Yao Fu, Tao Yu, Linghui Hu, Weihao Jiang, Shiliang Pu
-
Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining
Jaemin Yoo, Meng-Chieh Lee, Shubhranshu Shekhar, Christos Faloutsos
-
Task-Equivariant Graph Few-Shot Learning
Sungwon Kim, Junseok Lee, Namkyeong Lee, Wonjoong Kim, Seungyoon Choi, Chanyoung Park
-
GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning
Qianyue Hao, Wenzhen Huang, Tao Feng, Jian Yuan, Yong Li
-
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders
Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew Margenot, Hanghang Tong
-
DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection
Jiaying Wu, Bryan Hooi
-
FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs
Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-seng Chua, Qing He
-
A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability
Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du
-
Financial Default Prediction via Motif-Preserving Graph Neural Network with Curriculum Learning
Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou
-
Towards Reliable Rare Category Analysis on Graphs via Individual Calibration
Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou
-
QTIAH-GNN: Quantity and Topology Imbalance-Aware Heterogeneous Graph Neural Network for Bankruptcy Prediction
Yucheng Liu, Zipeng Gao, Xiangyang Liu, Pengfei Luo, Yang Yang, Hui Xiong; The Hong Kong University of Science and Technology
-
Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling
Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong
-
Locality Sensitive Hashing for Optimizing Subgraph Query Processing in Parallel Computing Systems
Peng Peng, Shengyi Ji, Zhen Tian, Hongbo Jiang, Weiguo Zheng, Xuecang Zhang
-
Efficient Distributed Approximate k-Nearest Neighbor Graph Construction by Multiway Random Division Forest
Sang-Hong Kim, Ha-Myung Park
-
Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds
Haoran Deng, Yang Yang, Jiahe Li, Haoyang Cai, Shiliang Pu, Weihao Jiang
-
DyTed: Disentangled Representation Learning for Discrete-Time Dynamic Graph
Kaike Zhang, Qi Cao, Gaolin Fang, Xu Bingbing, Hongjian Zou, Huawei Shen, Xueqi Cheng
-
Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation
Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang
-
WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window
Yifan Zhu, Fangpeng Cong, Dan Zhang, Wenwen Gong, Qika Lin, Wenzheng Feng, Yuxiao Dong, Jie Tang
-
EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation
Kuo Yang, Zhengyang Zhou, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang
-
Using Motif Transitions for Temporal Graph Generation
Penghang Liu, Ahmet Erdem Sariyuce
-
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks
Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan
-
Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks
Yaning Jia, Dongmian Zou, Hongfei Wang, Hai Jin
-
Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models
Kartik Sharma, Rakshit Trivedi, Rohit Sridhar, Srijan Kumar
-
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy
Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Cheng, Bing Yin, Suhang Wang
-
Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction
Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, LEI BAI, Yang Wang
-
Spatial Heterophily Aware Graph Neural Networks
Congxi Xiao, Jingbo Zhou, Jizhou Huang, Tong Xu, Hui Xiong; The Hong Kong University of Science and Technology
-
Leveraging Relational Graph Neural Network for Transductive Model Ensemble
Zhengyu Hu, Jieyu Zhang, Haonan Wang, Siwei Liu, Shangsong Liang
-
When to Pre-Train Graph Neural Networks? From Data Generation Perspective!
Yuxuan Cao, Jiarong Xu, Carl Yang, Jiaan Wang, Yunchao Zhang, Chunping Wang, Lei CHEN, Yang Yang
-
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities
Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang
-
Graph Neural Processes for Spatio-Temporal Extrapolation
Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann
-
Reconstructing Graph Diffusion History from a Single Snapshot
Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong
-
Generalizing Graph ODE for Learning Complex System Dynamics across Environments
Zijie Huang, Yizhou Sun, Wei Wang
-
B2-Sampling: Fusing Balanced and Biased Sampling for Graph Contrastive Learning
Mengyue Liu, Yun Lin, Jun Liu, Bohao Liu, Qinghua Zheng, Jin Song Dong
-
Similarity Preserving Adversarial Graph Contrastive Learning
Yeonjun In, Kanghoon Yoon, Chanyoung Park
-
HomoGCL: Rethinking Homophily in Graph Contrastive Learning
Wen-Zhi Li, Chang-Dong Wang, Hui Xiong; The Hong Kong University of Science and Technology), Jian-Huang Lai
-
Contrastive Cross-scale Graph Knowledge Synergy
Yifei Zhang, Yankai Chen, Zixing Song, Irwin King
-
Graph Contrastive Learning with Generative Adversarial Network
Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai
-
BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs
Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Rex Ying, Yukuo Cen, Yangliao Geng, Jie Tang
-
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing
Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu
-
Semi-Supervised Graph Imbalanced Regression
Gang Liu, Tong Zhao, Eric Inae, Tengfei Luo, Meng Jiang
-
Learning Joint Relational Co-Evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction
Youru Li, Zhenfeng Zhu, Xiaobo Guo, Linxun Chen, Zhouyin Wang, Yinmeng Wang, Bing Han, Yao Zhao
-
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection
Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory Madden, Daniel Borrajo, Jundong Li
-
Commonsense Knowledge Graph towards Supper APP and Its Applications in Alipay
Xiaoling Zang, Binbin Hu, Chu Jun, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong
-
Diga: Guided Diffusion Model for Graph Recovery in Anti-Money Laundering
Xujia Li, Yuan Li, Xueying Mo, Hebing Xiao, Yanyan Shen, Lei Chen; Hong Kong University of Science and Technology
-
DGI: An Easy and Efficient Framework for GNN Model Evaluation
Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang
-
Learning Multivariate Hawkes Process via Graph Recurrent Neural Network
Kanghoon Yoon, Youngjun Im, Jingyu Choi, Taehwan Jeong, Jinkyoo Park
-
HUGE: Huge Unsupervised Graph Embeddings with TPUs
Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi
-
Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs
Yuankai Luo, Lei Shi, Mufan Xu, Yuwen Ji, Fengli Xiao, Chunming Hu, Zhiguang Shan
-
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research
Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-mei Hwu
-
MIDLG: Mutual Information based Dual Level GNN for Transaction Fraud Complaint Verification
Wen Zheng, Bingbing Xu, Emiao Lu, Yang Li, Qi Cao, Xuan Zong, Huawei Shen
-
Graph Learning in Physical-Informed Mesh-Reduced Space for Real-World Dynamic Systems
Yeping Hu, Bo Lei, Victor M. Castillo
-
Knowledge Based Prohibited Item Detection on Heterogeneous Risk Graphs
Tingyan Xiang, Ao Li, Yugang Ji, Dong Li
-
TrustGeo: Uncertainty-Aware Dynamic Graph Learning for Trustworthy IP Geolocation
Wenxin Tai, Bin Chen, Fan Zhou, Ting Zhong, Goce Trajcevski, Yong Wang, Kai Chen
-
Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering
Xinyue Hu, Lin Gu, Qiyuan An, Zhang Mengliang, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu
-
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems
Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang
-
Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications
Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi
-
PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation
Xuewu Jiao, Weibin Li, Xinxuan Wu, Wei Hu, Miao Li, Jiang Bian, Siming Dai, Xinsheng Luo, Mingqing Hu, Zhengjie Huang, Danlei Feng, Junchao Yang, Shikun Feng, Haoyi Xiong, Dianhai Yu, Shuanglong Li, Jingzhou He, Yanjun Ma, Lin Liu
-
Adaptive Graph Contrastive Learning for Recommendation
Yangqin Jiang, Chao Huang, Lianghao Xia
-
Real Time Index and Search Across Large Quantities of GNN Experts For Low Latency Online Learning
Johan Zhi Kang Kok, Sien Yi Tan, Bingsheng He, Zhen Zhang
-
ILRoute: A Graph-based Imitation Learning Method to Unveil Riders’ Routing Strategies in Food Delivery Service
Tao Feng, Huan Yan, Huandong Wang, Wenzhen Huang, Yuyang Han, Hongsen Liao, Jinghua Hao, Yong Li
-
Deep Transfer Learning for City-Scale Cellular Traffic Generation through Urban Knowledge Graph
Zhang Shiyuan, Tong Li, Shuodi Hui, Guangyu Li, Yanping Liang, Li Yu, Depeng Jin, Yong Li
-
Adaptive Graph Representation Learning for Next POI Recommendation
Zhaobo Wang, Yanmin Zhu, Chunyang Wang, Wenze Ma, Bo Li, Jiadi Yu
-
Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering
Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou, Xiao Huang
-
Candidate–aware Graph Contrastive Learning for Recommendation
Wei He, Guohao Sun, Jinhu Lu, Xiu Susie Fang
-
Continual Learning on Dynamic Graphs via Parameter Isolation
Peiyan Zhang, Yuchen Yan, Chaozhuo Li, Senzhang Wang, Xing Xie, Guojie Song, Sunghun Kim
-
Contrastive Learning for Signed Bipartite Graphs
Zeyu Zhang, Jiamou Liu, Kaiqi Zhao, Song Yang, Xianda Zheng, Yifei Wang
-
Decoupled Hyperbolic Graph Attention Network for Cross-domain Named Entity Recognition
Jingyun Xu, Yi Cai
-
Distillation-Enhanced Graph Masked Autoencoders for Bundle Recommendation
Yuyang Ren, Zhang Haonan, Luoyi Fu, Xinbing Wang, Chenghu Zhou
-
DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning
Shangfei Zheng, Hongzhi Yin, Tong Chen, Quoc Viet Hung Nguyen, Wei Chen, Lei Zhao
-
Dynamic Graph Evolution Learning for Recommendation
Haoran Tang, Shiqing Wu, Guandong Xu, Qing Li
-
Generative-Contrastive Graph Learning for Recommendation
Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang
-
Graph Masked Autoencoder for Sequential Recommendation
Yaowen Ye, Lianghao Xia, Chao Huang
-
Knowledge-enhanced Multi-View Graph Neural Networks for Session-based Recommendation
Qian Chen, Zhiqiang Guo, Jianjun Li, Guohui Li
-
Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning
Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu
-
LightGT: A Light Graph Transformer for Multimedia Recommendation
Yinwei Wei, Wenqi Liu, Fan Liu, Xiang Wang, Liqiang Nie, Tat-Seng Chua
-
M2GNN: Metapath and Multi-interest Aggregated Graph Neural Network for Tag-based Cross-domain Recommendation
Zepeng Huai, Yuji Yang, Mengdi Zhang, Zhongyi Zhang, Yichun Li, Wei Wu
-
Graph Transformer for Recommendation
Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang
-
Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation
Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan, Fanyu Kong
-
Multi-order Matched Neighborhood Consistent Graph Alignment in a Union Vector Space
Wei Tang, Haifeng Sun, Jingyu Wang, Qi Qi, Jing Wang, Hao Yang, Shimin Tao
-
Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation
Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen, Dangyang Chen, Feida Zhu
-
Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network
Ran Li, Liang Zhang, Guannan Liu, Junjie Wu
-
Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
Linhao Luo, Reza Haffari, Yuan Fang Li, Shirui Pan
-
Relation-Aware Multi-Positive Contrastive Knowledge Graph Completion with Embedding Dimension Scaling
Bin Shang, Yinliang Zhao, Di Wang, Jun Liu
-
Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction
Yunzhi Yao, Shengyu Mao, Ningyu Zhang, Xiang Chen, Shumin Deng, Xi Chen, Huajun Chen
-
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph
Chenguang Du, Kaichun Yao, Hengshu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong
-
Session Search with Pre-trained Graph Classification Model
Shengjie Ma, Chong Chen, Jiaxin Mao, Qi Tian, Xuhui Jiang
-
Spatio-Temporal Hypergraph Learning for Next POI Recommendation
Xiaodong Yan, Tengwei Song, Yifeng Jiao, Jianshan He, Jiaotuan Wang, Ruopeng Li, Wei Chu
-
StreamE: Learning to Update Representations for Temporal Knowledge Graphs in Streaming Scenarios
Jiasheng Zhang, Jie Shao, Bin Cui
-
Subgraph Search over Neural-Symbolic Graphs
Ye Yuan, Delong Ma, Anbiao Wu, Jianbin Qin
-
Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis
Weibo Gao, Hao Wang, Qi Liu, Fei Wang, Xin Lin, Linan Yue, Zheng Zhang, Rui Lv, Shijin Wang
-
Time-interval Aware Share Recommendation via Bi-directional Continuous Time Dynamic Graphs
Ziwei Zhao, Xi Zhu, Tong Xu, Aakas Lizhiyu, Yu Yu, Xueying Li, Zikai Yin, Enhong Chen
-
Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation
Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong, Meng Wang
-
Weighted Knowledge Graph Embedding
Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang, Zhulin An, Fei Wang, Yongjun Xu
-
DeviceGPT: A Generative Pre-Training Transformer on the Heterogenous Graph for Internet of Things
Yimo Ren, Jinfa Wang, Hong Li, Hongsong Zhu, Limin Sun
-
DocGraphLM: Documental graph language model for information extraction
Dongsheng Wang, Zhiqiang Ma, Armineh Nourbakhsh, Kang Gu, Sameena Shah
-
Gated Attention with Asymmetric Regularization for Transformer-based Continual Graph Learning
Hongxiang Lin, Ruiqi Jia, Xiaoqing Lyu
-
Graph Collaborative Signals Denoising and Augmentation for Recommendation
Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu
-
Hierarchical Type Enhanced Negative Sampling for Knowledge Graph Embedding
Zhenzhou Lin, Zishuo Zhao, Jingyou Xie, Ying Shen
-
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraphs
Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
-
MDKG: Graph-Based Medical Knowledge-Guided Dialogue Generation
Usman Naseem, Surendrabikram Thapa, Qi Zhang, Liang Hu, Mehwish Nasim
-
Retrieval-Enhanced Generative Model for Large-Scale Knowledge Graph Completion
Donghan Yu, Yiming Yang
-
Sharpness-Aware Graph Collaborative Filtering
Huiyuan Chen, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Junpeng Wang, Vivian Lai, Mahashweta Das, Hao Yang
-
TrustSGCN: Learning Trustworthiness on Edge Signs for Effective Signed Graph Convolutional Networks
Min-Jeong Kim, Yeon-Chang Lee, Sang-Wook Kim
-
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework
Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi
-
WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering
Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma, Irwin King
-
(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More
Jan Schuchardt, Yan Scholten, Stephan Günnemann
-
4D Panoptic Scene Graph Generation
Jingkang Yang, Jun CEN, WENXUAN PENG, Shuai Liu, Fangzhou Hong, Xiangtai Li, Kaiyang Zhou, Qifeng Chen, Ziwei Liu
-
A Comparative Study of Graph Structure Learning: Benchmark and Analysis
Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Yu
-
A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking
Hao Yan, Chaozhuo Li, Ruosong Long, Chao Yan, Jianan Zhao, Wenwen Zhuang, Jun Yin, Peiyan Zhang, Weihao Han, Hao Sun, Weiwei Deng, Qi Zhang, Lichao Sun, Xing Xie, Senzhang Wang
-
A Fractional Graph Laplacian Approach to Oversmoothing
Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok
-
A Meta Learning Model for Scalable Hyperbolic Graph Neural Networks
Nurendra Choudhary, Nikhil Rao, Chandan Reddy
-
A Metadata-Driven Approach to Understand Graph Neural Networks
Ting Wei Li, Qiaozhu Mei, Jiaqi Ma
-
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks
Vignesh Kothapalli, Tom Tirer, Joan Bruna
-
A graphon-signal analysis of graph neural networks
Ron Levie
-
A new perspective on building efficient and expressive 3D equivariant graph neural networks
weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla Gomes, Zhi-Ming Ma
-
A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs
Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang
-
AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity
Jingyuan Li, Leo Scholl, Trung Le, Amy Orsborn, Eli Shlizerman
-
Accelerating Molecular Graph Neural Networks via Knowledge Distillation
Filip Ekström Kelvinius, Dimitar Georgiev, Artur Toshev, Johannes Gasteiger
-
Act As You Wish: Fine-grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs
Peng Jin, Yang Wu, Yanbo Fan, Zhongqian Sun, Wei Yang, Li Yuan
-
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Energy Conservation Approach
Kai Zhao, Yang Song, Qiyu Kang, Rui She, Sijie Wang, Wee Peng Tay
-
Adversarial Training for Graph Neural Networks
Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
-
Affinity-Aware Graph Networks
Ameya Velingker, Ali Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi
-
An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations
Haoran Yang, Xiangyu Zhao, Yicong Li, Hongxu Chen, Guandong Xu
-
Approximately Equivariant Graph Networks
Ningyuan Huang, Ron Levie, Soledad Villar
-
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning
Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang
-
AutoGO: Automated Computation Graph Optimization for Neural Network Evolution
Mohammad Salameh, Keith Mills, Negar Hassanpour, Fred Han, Shuting Zhang, Wei Lu, Shangling Jui, CHUNHUA ZHOU, Fengyu Sun, Di Niu
-
Bayesian Optimisation of Functions on Graphs
Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne, Xiaowen Dong
-
Better with Less: A Data-Centric Prespective on Pre-Training Graph Neural Networks
*Jiarong Xu, Renhong Huang, XIN JIANG, Yuxuan Cao, Carl Yang, Chunping Wang, YANG YANG*
-
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence
Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada
-
CAT-Walk: Inductive Hypergraph Learning via Set Walks
Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo Seltzer
-
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs
Yeyuan Chen, Dingmin Wang
-
Can Language Models Solve Graph Problems in Natural Language?
Heng Wang, Shangbin Feng, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, Yulia Tsvetkov
-
Certifiably Robust Graph Contrastive Learning
Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang
-
Characterization and Learning of Causal Graphs with Small Conditioning Sets
Murat Kocaoglu
-
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond
Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova
-
CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs
Guangyao Zhai, Evin Pınar Örnek, Shun-Cheng Wu, Yan Di, Federico Tombari, Nassir Navab, Benjamin Busam
-
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions
Duligur Ibeling, Thomas Icard
-
Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints
Jiaxin Bai, Xin Liu, Weiqi Wang, Chen Luo, Yangqiu Song
-
Curvature Filtrations for Graph Generative Model Evaluation
Joshua Southern, Jeremy Wayland, Michael Bronstein, Bastian Rieck
-
D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion
Jialin Chen, Shirley Wu, Abhijit Gupta, Rex Ying
-
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization
Zhiqing Sun, Yiming Yang
-
Data-Centric Learning from Unlabeled Graphs with Diffusion Model
Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang
-
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann
-
Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems
Fiona Lippert, Bart Kranstauber, Emiel van Loon, Patrick Forré
-
Deep Insights into Noisy Pseudo Labeling on Graph Data
Botao WANG, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, Fugee Tsung
-
Demystifying Oversmoothing in Attention-Based Graph Neural Networks
Xinyi Wu, Amir Ajorlou, Zihui Wu, Ali Jadbabaie
-
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
-
Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs
CHEN SHENGYUAN, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun
-
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection
Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Ozgur, Olgica Milenkovic
-
Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks
Xin Yan, Qiang He, Hui Fang
-
Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data
Saptarshi Roy, Raymond K. W. Wong, Yang Ni
-
Directional Diffusion Model for Graph Representation Learning
Run Yang, Yuling Yang, Fan Zhou, Qiang Sun
-
Does Graph Distillation See Like Vision Dataset Counterpart?
Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, Jianxin Li
-
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
-
Efficient Learning of Linear Graph Neural Networks via Node Subsampling
Seiyun Shin, Ilan Shomorony, Han Zhao
-
Enabling tabular deep learning when
$d \gg n$ with an auxiliary knowledge graphCamilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec
-
Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization
Haonan Yuan, Qingyun Sun, Xingcheng Fu, Ziwei Zhang, Cheng Ji, Hao Peng, Jianxin Li
-
Equivariant Neural Operator Learning with Graphon Convolution
Chaoran Cheng, Jian Peng
-
Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics
Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, Wenbing Huang
-
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
-
Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis
Junfeng Fang, Wei Liu, Xiang Wang, Zemin Liu, An Zhang, Yuan Gao, Xiangnan He
-
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts
Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova
-
Evaluating Self-Supervised Learning for Molecular Graph Embeddings
Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu
-
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes
Cai Zhou, Xiyuan Wang, Muhan Zhang
-
Fair Graph Distillation
Qizhang Feng, Zhimeng Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu
-
Fast Approximation of Similarity Graphs with Kernel Density Estimation
Peter Macgregor, He Sun
-
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks
Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong
-
Fine-grained Expressivity of Graph Neural Networks
Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris
-
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu
-
Fragment-based Pretraining and Finetuning on Molecular Graphs
Kha-Dinh Luong, Ambuj K Singh
-
From Trainable Negative Depth to Edge Heterophily in Graphs
Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong
-
Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge
Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu
-
Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications
Xinyu Ma, Xu Chu, Yasha Wang, Yang Lin, Junfeng Zhao, Liantao Ma, Wenwu Zhu
-
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li
-
GALOPA: Graph Transport Learning with Optimal Plan Alignment
Yejiang Wang, Yuhai Zhao, Daniel Zhengkui Wang, Ling Li
-
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning
Haiteng Zhao, Shengchao Liu, Ma Chang, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu
-
GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection
Namyong Park, Ryan Rossi, Xing Wang, Antoine Simoulin, Nesreen K. Ahmed, Christos Faloutsos
-
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels
Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan
-
Generalised f-Mean Aggregation for Graph Neural Networks
Ryan Kortvelesy, Steven D Morad, Amanda Prorok
-
Generative Pre-Training of Spatio-Temporal Graph Neural Networks
Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang
-
Geometric Analysis of Matrix Sensing over Graphs
Haixiang Zhang, Ying Chen, Javad Lavaei
-
Graph Clustering with Graph Neural Networks
Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
-
Graph Convolutional Kernel Machine versus Graph Convolutional Networks
Zhihao Wu, Zhao Zhang, Jicong Fan
-
Graph Denoising Diffusion for Inverse Protein Folding
Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang
-
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Kompella, Zhangyang "Atlas" Wang
-
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis
Abhinav Nippani, Dongyue Li, Haotian Ju, Haris Koutsopoulos, Hongyang Zhang
-
Graph of Circuits with GNN for Exploring the Optimal Design Space
Aditya Shahane, Saripilli Swapna Manjiri, Sandeep Kumar, Ankesh Jain
-
Graph-Structured Gaussian Processes for Transferable Graph Learning
Jun Wu, Lisa Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He
-
GraphACL: Simple Asymmetric Contrastive Learning of Graphs
Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang
-
GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph
Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen, Xinchao Wang
-
GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search
Xiao Zang, Miao Yin, Jinqi Xiao, Saman Zonouz, Bo Yuan
-
GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Node Patching
Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye
-
Graphs Contrastive Learning with Stable and Scalable Spectral Encoding
Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi
-
How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits
Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
-
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning
Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
-
Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion
Shengqiong Wu, Hao Fei, Hanwang Zhang, Tat-Seng Chua
-
Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
Yixiao Zhou, Ruiqi Jia, Xiaoqing Lyu, Yumeng Zhao, Hefeng Quan, Hongxiang Lin
-
Interpretable Graph Networks Formulate Universal Algebra Conjectures
Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Lupidi, Lucie Charlotte Magister, Pietro Lió, Pietro Barbiero
-
Interpretable Prototype-based Graph Information Bottleneck
Sangwoo Seo, Sungwon Kim, Chanyoung Park
-
Intervention Generalization: A View from Factor Graph Models
Gecia Bravo-Hermsdorff, David Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva
-
Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy
Lei Xu, Lei Chen, Rong Wang, Feiping Nie, Xuelong Li
-
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization
Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji
-
LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embedding
Ningyi Liao, Siqiang Luo, Xiang Li, Jieming Shi
-
Language Semantic Graph Guided Data-Efficient Learning
Wenxuan Ma, Shuang Li, lincan Cai, Jingxuan Kang
-
Large sample spectral analysis of graph-based multi-manifold clustering
Nicolas Garcia Trillos, Pengfei He, Chenghui Li
-
Latent Graph Inference with Limited Supervision
Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu
-
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park
-
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization
Xiao Wang, Donglin Xia, Nian Liu, Chuan Shi
-
Learning Large Graph Property Prediction via Graph Segment Training
Kaidi Cao, Phitchaya Phothilimtha, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi
-
Learning Latent Causal Graphs with Unknown Interventions
Yibo Jiang, Bryon Aragam
-
Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction
Tianyu Liu, Qitan Lv, Jie Wang, Shuling Yang, Hanzhu Chen
-
Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion
Kunxun Qi, Jianfeng Du, Hai Wan
-
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets
Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron Courville, Yoshua Bengio, Ling Pan
-
Limits, approximation and size transferability for GNNs on sparse graphs via graphops
Thien Le, Stefanie Jegelka
-
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference
Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding
-
Live Graph Lab: Towards Open, Dynamic and Real Transaction Graphs with NFT
Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He
-
LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees
Shangyuan LIU, Linglingzhi Zhu, Anthony Man-Cho So
-
Lovász Principle for Unsupervised Graph Representation Learning
Ziheng Sun, Chris Ding, Jicong Fan
-
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network
Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang
-
MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy
Honghua Dong, Jiawei Xu, Yu Yang, Rui Zhao, Shiwen Wu, Chun Yuan, Xiu Li, Chris Maddison, Lei Han
-
Mitigating the Popularity Bias in Graph-based Collaborative Filtering
Yifei Zhang, Hao Zhu, yankai Chen, Zixing Song, Piotr Koniusz, Irwin King
-
MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data
Tianyu Liu, Yuge Wang, Rex Ying, Hongyu Zhao
-
Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion
Hyuna Cho, Minjae Jeong, Sooyeon Jeon, Sungsoo Ahn, Won Hwa Kim
-
Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum
Yijian Qin, Xin Wang, Ziwei Zhang, Hong Chen, Wenwu Zhu
-
Network Regression with Graph Laplacians
Yidong Zhou, Hans-Georg Müller
-
Neural Graph Generation from Graph Statistics
Kiarash Zahirnia, Oliver Schulte, Mark Coates, Yaochen Hu
-
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem
Tal Amir, Steven Gortler, Ilai Avni, Ravina Ravina, Nadav Dym
-
Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data
Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song
-
NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics
Anwar Said, Roza Bayrak, Tyler Derr, Mudassir Shabbir, Daniel Moyer, Catie Chang, Xenofon Koutsoukos
-
Newton–Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems
Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun, Yixuan Lai, Qiang Zhang, Huajun Chen
-
No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning
Zixing Song, Yifei Zhang, Irwin King
-
On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data
Federico Errica
-
On Learning Necessary and Sufficient Causal Graphs
Hengrui Cai, Yixin Wang, Michael Jordan, Rui Song
-
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin, Tom Verbin, Nadav Cohen
-
On the Minimax Regret for Online Learning with Feedback Graphs
Khaled Eldowa, Emmanuel Esposito, Tom Cesari, Nicolò Cesa-Bianchi
-
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning
Zhou Zhiyao, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Can Wang, Yan Feng, Chun Chen
-
Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning
Zixing Song, Yifei Zhang, Irwin King
-
Optimality of Message-Passing Architectures for Sparse Graphs
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
-
Outlier-Robust Gromov Wasserstein for Graph Data
Lemin Kong, Jiajin Li, Jianheng Tang, Anthony Man-Cho So
-
PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis
Ali TehraniJamsaz, Quazi Ishtiaque Mahmud, Le Chen, Nesreen K. Ahmed, Ali Jannesari
-
PRODIGY: Enabling In-context Learning Over Graphs
Qian Huang, Hongyu Ren, Peng Chen, Gregor Kržmanc, Daniel Zeng, Percy Liang, Jure Leskovec
-
Partial Multi-Label Learning with Probabilistic Graphical Disambiguation
Jun-Yi Hang, Min-Ling Zhang
-
Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference
Ran Ran, Nuo Xu, Tao Liu, Wei Wang, Gang Quan, Wujie Wen
-
PlanE: Representation Learning over Planar Graphs
Radoslav Dimitrov, Zeyang Zhao, Ralph Abboud, Ismail Ceylan
-
Practical Contextual Bandits with Feedback Graphs
Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro
-
Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily
Langzhang Liang, Xiangjing Hu, Zenglin Xu, Zixing Song, Irwin King
-
Private subgraph counting using alternatives to global sensitivity
Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti
-
Provable Training for Graph Contrastive Learning
Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi
-
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals
Tingting Dan, Jiaqi Ding, Ziquan Wei, Shahar Kovalsky, Minjeong Kim, Won Hwa Kim, Guorong Wu
-
Recurrent Temporal Revision Graph Networks
Yizhou Chen, Anxiang Zeng, Qingtao Yu, Kerui Zhang, Cao Yuanpeng, Kangle Wu, Guangda Huzhang, Han Yu, Zhiming Zhou
-
Relational Curriculum Learning for Graph Neural Network
Zheng Zhang, Junxiang Wang, Liang Zhao
-
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules
ZHIYUAN LIU, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua
-
SPA: A Graph Spectral Alignment Perspective for Domain Adaptation
Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao
-
Self-supervised Graph Neural Networks via Low-Rank Decomposition
Liang Yang, Runjie Shi, Qiuliang Zhang, bingxin niu, Zhen Wang, Chuan Wang, Xiaochun Cao
-
Sheaf Hypergraph Networks
Iulia Duta, Giulia Cassarà, Fabrizio Silvestri, Pietro Lió
-
Simplifying and Empowering Transformers for Large-Graph Representations
Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
-
Sparse Graph Learning from Spatiotemporal Time Series
Andrea Cini, Daniele Zambon, Cesare Alippi
-
Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
Zeyang Zhang, Xin Wang, Ziwei Zhang, Zhou Qin, Weigao Wen, Hui Xue', Haoyang Li, Wenwu Zhu
-
Structure preserving reversible and irreversible bracket dynamics for deep graph neural networks
Anthony Gruber, Kookjin Lee, Nathaniel Trask
-
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data
Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan
-
SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network
Yuting Hu, Jiajie Li, Florian Klemme, Gi-Joon Nam, Tengfei Ma, Hussam Amrouch, Jinjun Xiong
-
TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph
Xueyuan Lin, Chengjin Xu, Haihong E, Fenglong Su, Gengxian Zhou, Tianyi Hu, Ningyuan Li, Mingzhi Sun, Haoran Luo
-
Tailoring Self-Attention for Graph via Rooted Subtrees
Siyuan Huang, Yunchong Song, Jiayue Zhou, Zhouhan Lin
-
Taming Local Effects in Graph-based Spatiotemporal Forecasting
Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi
-
TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery
Jialin Chen, Rex Ying
-
Temporal Graph Benchmark for Machine Learning on Temporal Graphs
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
-
The Graphical Matrix Pencil Method: Exchangeable Distributions with Prescribed Subgraph Densities
Lee Gunderson, Gecia Bravo-Hermsdorff, Peter Orbanz
-
The expressive power of pooling in Graph Neural Networks
Filippo Maria Bianchi, Veronica Lachi
-
Towards Better Dynamic Graph Learning: New Architecture and Unified Library
Le Yu, Leilei Sun, Bowen Du, Weifeng Lv
-
Towards Label Position Bias in Graph Neural Networks
Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu Aggarwal, Jiliang Tang
-
Towards Self-Interpretable Graph-Level Anomaly Detection
Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan
-
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs
Phitchaya Phothilimtha, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Charith Mendis, Bryan Perozzi
-
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks
Jun Yin, Senzhang Wang, Hao Yan, Chaozhuo Li, Jianxun Lian
-
Transformers over Directed Acyclic Graphs
Yuankai Luo, Veronika Thost, Lei Shi
-
Truncated Affinity Maximization for Graph Anomaly Detection
Hezhe Qiao, Guansong Pang
-
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction
Yansong Ning, Hao Liu, Hao Wang, Zhenyu Zeng, Hui Xiong
-
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks
Kexin Huang, Ying Jin, Emmanuel Candes, Jure Leskovec
-
Universal Prompt Tuning for Graph Neural Networks
Taoran Fang, Yunchao Zhang, YANG YANG, Chunping Wang, Lei Chen
-
Unleashing the Power of Graph Data Augmentation on Covariate Shift
Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He
-
Unsupervised Graph Neural Architecture Search with Disentangled Self-Supervision
Zeyang Zhang, Xin Wang, Ziwei Zhang, Guangyao Shen, Shiqi Shen, Wenwu Zhu
-
V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs
Jun Yin, Senzhang Wang, Chaozhuo Li, Xing Xie, Jianxin Wang
-
Variational Annealing on Graphs for Combinatorial Optimization
Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner
-
Video-Mined Task Graphs for Keystep Recognition in Instructional Videos
Kumar Ashutosh, Santhosh Kumar Ramakrishnan, Triantafyllos Afouras, Kristen Grauman
-
WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding
Yanchao Tan, Zihao Zhou, Hang Lv, Weiming Liu, Carl Yang
-
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding
Nicolas Keriven, Samuel Vaiter
-
When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability
Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup
-
Zero-One Laws of Graph Neural Networks
Sam Adam-Day, Iliant, Ismail Ceylan
-
[Re]
$\mathcal{G}$ -Mixup: Graph Data Augmentation for Graph ClassificationErmin Omeragic, Vuk Đuranović
-
[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
Yannik Mahlau, Lukas Berg, Leonie Kayser
-
Knowledge Graphs for Knowing More and Knowing for Sure
Steffen Staab
-
Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs
Medina Andresel, Trung-Kien Tran, Csaba Domokos, Pasquale Minervini, Daria Stepanova
-
GraphERT-- Transformers-based Temporal Dynamic Graph Embedding
Moran Beladev, Gilad Katz, Lior Rokach, Uriel Singer, Kira Radinsky
-
Faster Approximation Algorithms for Parameterized Graph Clustering and Edge Labeling
Vedangi Bengali, Nate Veldt
-
Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer
Wendong Bi, Xueqi Cheng, Bingbing Xu, Xiaoqian Sun, Li Xu, Huawei Shen
-
How Expressive are Graph Neural Networks in Recommendation?
Xuheng Cai, Lianghao Xia, Xubin Ren, Chao Huang
-
Learning Pair-Centric Representation for Link Sign Prediction with Subgraph
Jushuo Chen, Feifei Dai, Xiaoyan Gu, Haihui Fan, Jiang Zhou, Bo Li, Weiping Wang
-
Can Knowledge Graphs Simplify Text?
Anthony Colas, Haodi Ma, Xuanli He, Yang Bai, Daisy Zhe Wang
-
Cross-heterogeneity Graph Few-shot Learning
Pengfei Ding, Yan Wang, Guanfeng Liu
-
Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training
Ziwei Fan, Zhiwei Liu, Shelby Heinecke, Jianguo Zhang, Huan Wang, Caiming Xiong, Philip S. Yu
-
Spatial-Temporal Graph Boosting Networks: Enhancing Spatial-Temporal Graph Neural Networks via Gradient Boosting
Yujie Fan, Chin-Chia Michael Yeh, Huiyuan Chen, Yan Zheng, Liang Wang, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Wei Zhang
-
BOMGraph: Boosting Multi-scenario E-commerce Search with a Unified Graph Neural Network
Shuai Fan, Jinping Gou, Yang Li, Jiaxing Bai, Chen Lin, Wanxian Guan, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng
-
Cognitive-inspired Graph Redundancy Networks for Multi-source Information Fusion
Yao Fu, Junhong Wan, Junlan Yu, Weihao Jiang, Shiliang Pu
-
On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks
Jhony H. Giraldo, Konstantinos Skianis, Thierry Bouwmans, Fragkiskos D. Malliaros
-
Homophily-enhanced Structure Learning for Graph Clustering
Ming Gu, Gaoming Yang, Sheng Zhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu
-
KG4Ex: An Explainable Knowledge Graph-Based Approach for Exercise Recommendation
Quanlong Guan, Fang Xiao, Xinghe Cheng, Liangda Fang, Ziliang Chen, Guanliang Chen, Weiqi Luo
-
Targeted Shilling Attacks on GNN-based Recommender Systems
Sihan Guo, Ting Bai, Weihong Deng
-
Interpretable Fake News Detection with Graph Evidence
Hao Guo, Weixin Zeng, Jiuyang Tang, Xiang Zhao
-
Towards Fair Graph Neural Networks via Graph Counterfactual
Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang
-
Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning
Xinrui He, Tianxin Wei, Jingrui He
-
Celebrity-aware Graph Contrastive Learning Framework for Social Recommendation
Zheng Hu, Satoshi Nakagawa, Liang Luo, Yu Gu, Fuji Ren
-
HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li, Jeff Z. Pan
-
Enhanced Template-Free Reaction Prediction with Molecular Graphs and Sequence-based Data Augmentation
Haozhe Hu, Yongquan Jiang, Yan Yang, Jim X. Chen
-
Independent Distribution Regularization for Private Graph Embedding
Qi Hu, Yangqiu Song
-
Liberate Pseudo Labels from Over-Dependence: Label Information Migration on Sparsely Labeled Graphs
Zhihui Hu, Yao Fu, Hong Zhao, Xiaoyu Cai, Weihao Jiang, Shiliang Pu
-
Relevant Entity Selection: Knowledge Graph Bootstrapping via Zero-Shot Analogical Pruning
Lucas Jarnac, Miguel Couceiro, Pierre Monnin
-
Robust Graph Clustering via Meta Weighting for Noisy Graphs
Hyeonsoo Jo, Fanchen Bu, Kijung Shin
-
A Model-Agnostic Method to Interpret Link Prediction Evaluation of Knowledge Graph Embeddings
Narayanan Asuri Krishnan, Carlos R. Rivero
-
A Re-evaluation of Deep Learning Methods for Attributed Graph Clustering
Xinying Lai, Dingming Wu, Christian S. Jensen, Kezhong Lu
-
DuoGAT: Dual Time-oriented Graph Attention Networks for Accurate, Efficient and Explainable Anomaly Detection on Time-series
Jongsoo Lee, Byeongtae Park, Dong-Kyu Chae
-
GUARD: Graph Universal Adversarial Defense
Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang
-
ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural Networks
Yiqiao Li, Jianlong Zhou, Yifei Dong, Niusha Shafiabady, Fang Chen
-
Heterogeneous Temporal Graph Neural Network Explainer
Jiazheng Li, Chunhui Zhang, Chuxu Zhang
-
Graph Enhanced Hierarchical Reinforcement Learning for Goal-oriented Learning Path Recommendation
Qingyao Li, Wei Xia, Li'ang Yin, Jian Shen, Renting Rui, Weinan Zhang, Xianyu Chen, Ruiming Tang, Yong Yu
-
Contrastive Representation Learning Based on Multiple Node-centered Subgraphs
Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao
-
Multi-Order Relations Hyperbolic Fusion for Heterogeneous Graphs
Junlin Li, Yueheng Sun, Minglai Shao
-
THGNN: An Embedding-based Model for Anomaly Detection in Dynamic Heterogeneous Social Networks
Yilin Li, Jiaqi Zhu, Congcong Zhang, Yi Yang, Jiawen Zhang, Ying Qiao, Hongan Wang
-
Retrieving GNN Architecture for Collaborative Filtering
Fengqi Liang, Huan Zhao, Zhenyi Wang, Wei Fang, Chuan Shi
-
printf: Preference Modeling Based on User Reviews with Item Images and Textual Information via Graph Learning
Hao-Lun Lin, Jyun-Yu Jiang, Ming-Hao Juan, Pu-Jen Cheng
-
MATA: Combining Learnable Node Matching with A Algorithm for Approximate Graph Edit Distance Computation**
Junfeng Liu, Min Zhou, Shuai Ma, Lujia Pan
-
ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding
Zixuan Liu, Gaurush Hiranandani, Kun Qian, Edward W. Huang, Yi Xu, Belinda Zeng, Karthik Subbian, Sheng Wang
-
SMEF: Social-aware Multi-dimensional Edge Features-based Graph Representation Learning for Recommendation
Xiao Liu, Shunmei Meng, Qianmu Li, Lianyong Qi, Xiaolong Xu, Wanchun Dou, Xuyun Zhang
-
Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph
Yi Liu, Hongrui Xuan, Bohan Li, Meng Wang, Tong Chen, Hongzhi Yin
-
BRep-BERT: Pre-training Boundary Representation BERT with Sub-graph Node Contrastive Learning
Yunzhong Lou, Xueyang Li, Haotian Chen, Xiangdong Zhou
-
Timestamps as Prompts for Geography-Aware Location Recommendation
Yan Luo, Haoyi Duan, Ye Liu, Fu-Lai Chung
-
Improving Long-Tail Item Recommendation with Graph Augmentation
Sichun Luo, Chen Ma, Yuanzhang Xiao, Linqi Song
-
Multi-scale Graph Pooling Approach with Adaptive Key Subgraph for Graph Representations
Yiqin Lv, Zhiliang Tian, Zheng Xie, Yiping Song
-
A Graph Neural Network Model for Concept Prerequisite Relation Extraction
Debjani Mazumder, Jiaul H. Paik, Anupam Basu
-
Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification
Arpit Merchant, Carlos Castillo
-
Rule-based Knowledge Graph Completion with Canonical Models
Simon Ott, Patrick Betz, Daria Stepanova, Mohamed H. Gad-Elrab, Christian Meilicke, Heiner Stuckenschmidt
-
A Retrieve-and-Read Framework for Knowledge Graph Link Prediction
Vardaan Pahuja, Boshi Wang, Hugo Latapie, Jayanth Srinivasa, Yu Su
-
Bi-channel Multiple Sparse Graph Attention Networks for Session-based Recommendation
Shutong Qiao, Wei Zhou, Junhao Wen, Hongyu Zhang, Min Gao
-
ELTRA: An Embedding Method based on Learning-to-Rank to Preserve Asymmetric Information in Directed Graphs
Masoud Rehyani Hamedani, Jin-Su Ryu, Sang-Wook Kim
-
Dual-Process Graph Neural Network for Diversified Recommendation
Yuanyi Ren, Hang Ni, Yingxue Zhang, Xi Wang, Guojie Song, Dong Li, Jianye Hao
-
Incremental Graph Classification by Class Prototype Construction and Augmentation
Yixin Ren, Li Ke, Dong Li, Hui Xue, Zhao Li, Shuigeng Zhou
-
Seq-HyGAN: Sequence Classification via Hypergraph Attention Network
Khaled Mohammed Saifuddin, Corey May, Farhan Tanvir, Muhammad Ifte Khairul Islam, Esra Akbas
-
Transferable Structure-based Adversarial Attack of Heterogeneous Graph Neural Network
Yu Shang, Yudong Zhang, Jiansheng Chen, Depeng Jin, Yong Li
-
Improving Graph Domain Adaptation with Network Hierarchy
Boshen Shi, Yongqing Wang, Fangda Guo, Jiangli Shao, Huawei Shen, Xueqi Cheng
-
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction
Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu
-
Calibrate Graph Neural Networks under Out-of-Distribution Nodes via Deep Q-learning
Weili Shi, Xueying Yang, Xujiang Zhao, Haifeng Chen, Zhiqiang Tao, Sheng Li
-
Towards Fair Financial Services for All: A Temporal GNN Approach for Individual Fairness on Transaction Networks
Zixing Song, Yuji Zhang, Irwin King
-
Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data
Xiao Tan, Yangyang Shen, Meng Wang, Beilun Wang
-
Explainable Spatio-Temporal Graph Neural Networks
Jiabin Tang, Lianghao Xia, Chao Huang
-
Citation Intent Classification and Its Supporting Evidence Extraction for Citation Graph Construction
Hong-Jin Tsai, An-Zi Yen, Hen-Hsen Huang, Hsin-Hsi Chen
-
Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation
Ke Tu, Wei Qu, Zhengwei Wu, Zhiqiang Zhang, Zhongyi Liu, Yiming Zhao, Le Wu, Jun Zhou, Guannan Zhang
-
GraphFADE: Field-aware Decorrelation Neural Network for Graphs with Tabular Features
Junhong Wan, Yao Fu, Junlan Yu, Weihao Jiang, Shiliang Pu, Ruiheng Yang
-
UrbanFloodKG: An Urban Flood Knowledge Graph System for Risk Assessment
Yu Wang, Feng Ye, Binquan Li, Gaoyang Jin, Dong Xu, Fengsheng Li
-
Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation
Shuang Wang, Bahaeddin Eravci, Rustam Guliyev, Hakan Ferhatosmanoglu
-
Node-dependent Semantic Search over Heterogeneous Graph Neural Networks
Zhenyi Wang, Huan Zhao, Fengqi Liang, Chuan Shi
-
Dual Intents Graph Modeling for User-centric Group Discovery
Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang
-
SplitGNN: Spectral Graph Neural Network for Fraud Detection against Heterophily
Bin Wu, Xinyu Yao, Boyan Zhang, Kuo-Ming Chao, Yinsheng Li
-
DPGN: Denoising Periodic Graph Network for Life Service Recommendation
Hao Xu, Huixuan Chi, Danyang Liu, Sheng Zhou, Mengdi Zhang
-
A Bipartite Graph is All We Need for Enhancing Emotional Reasoning with Commonsense Knowledge
Kailai Yang, Tianlin Zhang, Shaoxiong Ji, Sophia Ananiadou
-
Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning
Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu
-
Causality-guided Graph Learning for Session-based Recommendation
Dianer Yu, Qian Li, Hongzhi Yin, Guandong Xu
-
MUSE: Multi-view Contrastive Learning for Heterophilic Graphs via Information Reconstruction
Mengyi Yuan, Minjie Chen, Xiang Li
-
AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange
Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li
-
RDGSL: Dynamic Graph Representation Learning with Structure Learning
Siwei Zhang, Yun Xiong, Yao Zhang, Yiheng Sun, Xi Chen, Yizhu Jiao, Yangyong Zhu
-
iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation
Siwei Zhang, Yun Xiong, Yao Zhang, Xixi Wu, Yiheng Sun, Jiawei Zhang
-
Time-aware Graph Structure Learning via Sequence Prediction on Temporal Graphs
Haozhen Zhang, Xueting Han, Xi Xiao, Jing Bai
-
AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities
Jingdan Zhang, Jiaan Wang, Xiaodan Wang, Zhixu Li, Yanghua Xiao
-
Efficient Exact Minimum k-Core Search in Real-World Graphs
Qifan Zhang, Shengxin Liu
-
HST-GT: Heterogeneous Spatial-Temporal Graph Transformer for Delivery Time Estimation in Warehouse-Distribution Integration E-Commerce
Xiaohui Zhao, Shuai Wang, Hai Wang, Tian He, Desheng Zhang, Guang Wang
-
Geometric Graph Learning for Protein Mutation Effect Prediction
Kangfei Zhao, Yu Rong, Biaobin Jiang, Jianheng Tang, Hengtong Zhang, Jeffrey Xu Yu, Peilin Zhao
-
Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs
Tianyi Zhao, Hui Hu, Lu Cheng
-
Decentralized Graph Neural Network for Privacy-Preserving Recommendation
Xiaolin Zheng, Zhongyu Wang, Chaochao Chen, Jiashu Qian, Yao Yang
-
G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer
Yuchen Zhuang, Xin Shen, Yan Zhao, Chaosheng Dong, Ming Wang, Jin Li, Chao Zhang
-
HOVER: Homophilic Oversampling via Edge Removal for Class-Imbalanced Bot Detection on Graphs
Bradley Ashmore, Lingwei Chen
-
Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction
Yuanchen Bei, Hao Chen, Shengyuan Chen, Xiao Huang, Sheng Zhou, Feiran Huang
-
Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems
Ludovico Boratto, Francesco Fabbri, Gianni Fenu, Mirko Marras, Giacomo Medda
-
Self-supervised Learning and Graph Classification under Heterophily
Yilin Ding, Zhen Liu, Hao Hao
-
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network
Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong
-
KGPR: Knowledge Graph Enhanced Passage Ranking
Jinyuan Fang, Zaiqiao Meng, Craig Macdonald
-
Neighborhood Homophily-based Graph Convolutional Network
Shengbo Gong, Jiajun Zhou, Chenxuan Xie, Qi Xuan
-
KGrEaT: A Framework to Evaluate Knowledge Graphs via Downstream Tasks
Nicolas Heist, Sven Hertling, Heiko Paulheim
-
Stochastic Subgraph Neighborhood Pooling for Subgraph Classification
Shweta Ann Jacob, Paul Louis, Amirali Salehi-Abari
-
S-Mixup: Structural Mixup for Graph Neural Networks
Junghurn Kim, Sukwon Yun, Chanyoung Park
-
Class Label-aware Graph Anomaly Detection
Junghoon Kim, Yeonjun In, Kanghoon Yoon, Junmo Lee, Chanyoung Park
-
Exploring Cohesive Subgraphs in Hypergraphs: The (k,g)-core Approach
Dahee Kim, Junghoon Kim, Sungsu Lim, Hyun Ji Jeong
-
Towards Trustworthy Rumor Detection with Interpretable Graph Structural Learning
Leyuan Liu, Junyi Chen, Zhangtao Cheng, Wenxin Tai, Fan Zhou
-
Boosting Meta-Learning Cold-Start Recommendation with Graph Neural Network
Han Liu, Hongxiang Lin, Xiaotong Zhang, Fenglong Ma, Hongyang Chen, Lei Wang, Hong Yu, Xianchao Zhang
-
STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation
Shaohua Liu, Yu Qi, Gen Li, Mingjian Chen, Teng Zhang, Jia Cheng, Jun Lei
-
FairGraph: Automated Graph Debiasing with Gradient Matching
Yezi Liu
-
DCGNN: Dual-Channel Graph Neural Network for Social Bot Detection
Nuoyan Lyu, Bingbing Xu, Fangda Guo, Huawei Shen
-
Metapath-Guided Data-Augmentation For Knowledge Graphs
Saurav Manchanda
-
Learning Visibility Attention Graph Representation for Time Series Forecasting
Shengzhong Mao, Xiao-Jun Zeng
-
Graph Contrastive Learning with Graph Info-Min
En Meng, Yong Liu
-
Generative Graph Augmentation for Minority Class in Fraud Detection
Lin Meng, Hesham Mostafa, Marcel Nassar, Xiaonan Zhang, Jiawei Zhang
-
Efficient Differencing of System-level Provenance Graphs
Yuta Nakamura, Iyad Kanj, Tanu Malik
-
VN-Solver: Vision-based Neural Solver for Combinatorial Optimization over Graphs
Mina Samizadeh, Guangmo Tong
-
Network Embedding with Adaptive Multi-hop Contrast
Chenhao Wang, Yong Liu, Yan Yang
-
Training Heterogeneous Graph Neural Networks using Bandit Sampling
Ta-Yang Wang, Rajgopal Kannan, Viktor Prasanna
-
Adaptive Graph Neural Diffusion for Traffic Demand Forecasting
Yiling Wu, Xinfeng Zhang, Yaowei Wang
-
Geometry Interaction Augmented Graph Collaborative Filtering
Jie Xu, Chaozhuo Li
-
Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning
Tianmeng Yang, Min Zhou, Yujing Wang, Zhengjie Lin, Lujia Pan, Bin Cui, Yunhai Tong
-
Positive-Unlabeled Node Classification with Structure-aware Graph Learning
Hansi Yang, Yongqi Zhang, Quanming Yao, James Kwok
-
Graph-based Alignment and Uniformity for Recommendation
Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu
-
BI-GCN: Bilateral Interactive Graph Convolutional Network for Recommendation
Yinan Zhang, Pei Wang, Congcong Liu, Xiwei Zhao, Hao Qi, Jie He, Junsheng Jin, Changping Peng, Zhangang Lin, Jingping Shao
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Knowledge Graph Error Detection with Hierarchical Path Structure
Zhao Zhang, Fuwei Zhang, Fuzhen Zhuang, Yongjun Xu
-
Weight Matters: An Empirical Investigation of Distance Oracles on Knowledge Graphs
Ke Zhang, Jiageng Chen, Zixian Huang, Gong Cheng
-
LEAD-ID: Language-Enhanced Denoising and Intent Distinguishing Graph Neural Network for Sponsored Search Broad Retrievals
Xiao Zhou, Ran Wang, Haorui Li, Qiang Liu, Xingxing Wang, Dong Wang
-
CallMine: Fraud Detection and Visualization of Million-Scale Call Graphs
Mirela Cazzolato, Saranya Vijayakumar, Meng-Chieh Lee, Catalina Vajiac, Namyong Park, Pedro Fidalgo, Agma J.M. Traina, Christos Faloutsos
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Enhancing Catalog Relationship Problems with Heterogeneous Graphs and Graph Neural Networks Distillation
Boxin Du, Rob Barton, Grant Galloway, Junzhou Huang, Shioulin Sam, Ismail Tutar, Changhe Yuan
-
FAF: A Risk Detection Framework on Industry-Scale Graphs
Yice Luo, Guannan Wang, Yongchao Liu, Jiaxin Yue, Weihong Cheng, Binjie Fei
-
Graph Learning for Exploratory Query Suggestions in an Instant Search System
Enrico Palumbo, Andreas Damianou, Alice Wang, Alva Liu, Ghazal Fazelnia, Francesco Fabbri, Rui Ferreira, Fabrizio Silvestri, Hugues Bouchard, Claudia Hauff, Mounia Lalmas, Ben Carterette, Praveen Chandar, David Nyhan
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GBTTE: Graph Attention Network Based Bus Travel Time Estimation
Yuecheng Rong, Juntao Yao, Jun Liu, Yifan Fang, Wei Luo, Hao Liu, Jie Ma, Zepeng Dan, Jinzhu Lin, Zhi Wu, Yan Zhang, Chuanming Zhang
-
GraphFC: Customs Fraud Detection with Label Scarcity
Karandeep Singh, Yu-Che Tsai, Cheng-Te Li, Meeyoung Cha, Shou-De Lin
-
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks
Zhihao Wen, Yuan Fang, Yihan Liu, Yang Guo, Shuji Hao
-
Logistics Audience Expansion via Temporal Knowledge Graph
Hua Yan, Yingqiang Ge, Haotian Wang, Desheng Zhang, Yu Yang
-
Graph Exploration Matters: Improving both Individual-Level and System-Level Diversity in WeChat Feed Recommendation
Shuai Yang, Lixin Zhang, Feng Xia, Leyu Lin
-
Multi-gate Mixture-of-Contrastive-Experts with Graph-based Gating Mechanism for TV Recommendation
Cong Zhang, Dongyang Liu, Lin Zuo, Junlan Feng, Chao Deng, Jian Sun, Haitao Zeng, Yaohong Zhao
-
Dual Interests-Aligned Graph Auto-Encoders for Cross-domain Recommendation in WeChat
Jiawei Zheng, Hao Gu, Chonggang Song, Dandan Lin, Lingling Yi, Chuan Chen
-
The µ-RA System for Recursive Path Queries over Graphs
Amela Fejza, Pierre Genevès, Nabil Layaïda, Sarah Chlyah
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Investigating Natural and Artificial Dynamics in Graph Data Mining and Machine Learning
Dongqi Fu
-
A Neuro-symbolic Approach to Enhance Interpretability of Graph Neural Network through the Integration of External Knowledge
Kislay Raj
-
Exploiting Homeostatic Synaptic Modulation in Spiking Neural Networks for Semi-Supervised Graph Learning
Mingkun Xu
-
Leveraging Graph Neural Networks for User Profiling: Recent Advances and Open Challenges
Erasmo Purificato, Ludovico Boratto, Ernesto William De Luca
-
Reasoning beyond Triples: Recent Advances in Knowledge Graph Embeddings
Bo Xiong, Mojtaba Nayyeri, Daniel Daza, Michael Cochez
-
From User Activity Traces to Navigation Graph for Software Enhancement: An Application of Graph Neural Network (GNN) on a Real-World Non-Attributed Graph
Ikram Boukharouba, Florence Sèdes, Christophe Bortolaso, Florent Mouysset
-
Astrolabe: Visual Graph Database Queries with Tabular Output
Michael Miller
-
Workshop on Enterprise Knowledge Graphs using Large Language Models
Rajeev Gupta, Srinath Srinivasa
-
PGB: A PubMed Graph Benchmark for Heterogeneous Network Representation Learning
Eric W. Lee, Joyce C. Ho
-
Datasets and Interfaces for Benchmarking Heterogeneous Graph Neural Networks
Yijian Liu, Hongyi Zhang, Cheng Yang, Ao Li, Yugang Ji, Luhao Zhang, Tao Li, Jinyu Yang, Tianyu Zhao, Juan Yang, Hai Huang, Chuan Shi
-
OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning
Boshen Shi, Yongqing Wang, Fangda Guo, Jiangli Shao, Huawei Shen, Xueqi Cheng
-
Self-Supervised Graph Learning for Long-Tailed Cognitive Diagnosis
Shanshan Wang, Zhen Zeng, Xun Yang, Xingyi Zhang
-
Exposing the Self-Supervised Space-Time Correspondence Learning via Graph Kernels
Zheyun Qin, Xiankai Lu, Xiushan Nie, Yilong Yin, Jianbing Shen
-
Asynchronous Event Processing with Local-Shift Graph Convolutional Network
Linhui Sun, Yifan Zhang, Jian Cheng, Hanqing Lu
-
Multi-Modal Knowledge Hypergraph for Diverse Image Retrieval
Yawen Zeng, Qin Jin, Tengfei Bao, Wenfeng Li
-
MulGT: Multi-Task Graph-Transformer with Task-Aware Knowledge Injection and Domain Knowledge-Driven Pooling for Whole Slide Image Analysis
Weiqin Zhao, Shujun Wang, Maximus Yeung, Tianye Niu, Lequan Yu
-
Separate but Equal: Equality in Belief Propagation for Single Cycle Graphs
Erel Cohen, Omer Lev, Roie Zivan
-
Enhanced Multi-Relationships Integration Graph Convolutional Network for Inferring Substitutable and Complementary Items
Huajie Chen, Jiyuan He, Weisheng Xu, Tao Feng, Ming Liu, Tianyu Song, Runfeng Yao, Yuanyuan Qiao
-
Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding
Mingyang Chen, Wen Zhang, Zhen Yao, Yushan Zhu, Yang Gao, Jeff Z. Pan, Huajun Chen
-
Dual Low-Rank Graph Autoencoder for Semantic and Topological Networks
Zhaoliang Chen, Zhihao Wu, Shiping Wang, Wenzhong Guo
-
Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction
Chanyoung Chung, Joyce Jiyoung Whang
-
Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs
Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han, Wei Hu
-
DropMessage: Unifying Random Dropping for Graph Neural Networks
Taoran Fang, Zhiqing Xiao, Chunping Wang, Jiarong Xu, Xuan Yang, Yang Yang
-
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning
Xumeng Gong, Cheng Yang, Chuan Shi
-
Generic and Dynamic Graph Representation Learning for Crowd Flow Modeling
Liangzhe Han, Ruixing Zhang, Leilei Sun, Bowen Du, Yanjie Fu, Tongyu Zhu
-
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation
Han Huang, Leilei Sun, Bowen Du, Weifeng Lv
-
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation
Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu
-
Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning
Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye
-
GLCC: A General Framework for Graph-Level Clustering
Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang
-
Signed Laplacian Graph Neural Networks
Yu Li, Meng Qu, Jian Tang, Yi Chang
-
Scalable and Effective Conductance-Based Graph Clustering
Longlong Lin, Ronghua Li, Tao Jia
-
Multi-Domain Generalized Graph Meta Learning
Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, Guohao Li, Sanglu Lu
-
IterDE: An Iterative Knowledge Distillation Framework for Knowledge Graph Embeddings
Jiajun Liu, Peng Wang, Ziyu Shang, Chenxiao Wu
-
Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
Yixin Liu, Yizhen Zheng, Daokun Zhang, Vincent CS Lee, Shirui Pan
-
On Generalized Degree Fairness in Graph Neural Networks
Zemin Liu, Trung-Kien Nguyen, Yuan Fang
-
Graph Structure Learning on User Mobility Data for Social Relationship Inference
Guangming Qin, Lexue Song, Yanwei Yu, Chao Huang, Wenzhe Jia, Yuan Cao, Junyu Dong
-
Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces
Li Sun, Junda Ye, Hao Peng, Feiyang Wang, Philip S. Yu
-
Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information
Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu
-
Easy Begun Is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout
Hongjun Wang, Jiyuan Chen, Tong Pan, Zipei Fan, Xuan Song, Renhe Jiang, Lingyu Zhang, Yi Xie, Zhongyi Wang, Boyuan Zhang
-
Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment
Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray Buntine, Christopher Leckie
-
Beyond Graph Convolutional Network: An Interpretable Regularizer-Centered Optimization Framework
Shiping Wang, Zhihao Wu, Yuhong Chen, Yong Chen
-
Augmenting Affective Dependency Graph via Iterative Incongruity Graph Learning for Sarcasm Detection
Xiaobao Wang, Yiqi Dong, Di Jin, Yawen Li, Longbiao Wang, Jianwu Dang
-
Temporal Knowledge Graph Reasoning with Historical Contrastive Learning
Yi Xu, Junjie Ou, Hui Xu, Luoyi Fu
-
Next POI Recommendation with Dynamic Graph and Explicit Dependency
Feiyu Yin, Yong Liu, Zhiqi Shen, Lisi Chen, Shuo Shang, Peng Han
-
Learning to Count Isomorphisms with Graph Neural Networks
Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang
-
Cross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator
Qiannan Zhang, Shichao Pei, Qiang Yang, Chuxu Zhang, Nitesh V. Chawla, Xiangliang Zhang
-
Deep Graph Structural Infomax
Wenting Zhao, Gongping Xu, Zhen Cui, Siqiang Luo, Cheng Long, Tong Zhang
-
A Provable Framework of Learning Graph Embeddings via Summarization
Houquan Zhou, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng
-
GraphSR: A Data Augmentation Algorithm for Imbalanced Node Classification
Mengting Zhou, Zhiguo Gong
-
GRLSTM: Trajectory Similarity Computation with Graph-Based Residual LSTM
Silin Zhou, Jing Li, Hao Wang, Shuo Shang, Peng Han
-
Heterogeneous Graph Learning for Multi-Modal Medical Data Analysis
Sein Kim, Namkyeong Lee, Junseok Lee, Dongmin Hyun, Chanyoung Park
-
GRIP: Graph Representation of Immune Repertoire Using Graph Neural Network and Transformer
Yongju Lee, Hyunho Lee, Kyoungseob Shin, Sunghoon Kwon
-
Molformer: Motif-Based Transformer on 3D Heterogeneous Molecular Graphs
Fang Wu, Dragomir Radev, Stan Z. Li
-
Multi-Relational Contrastive Learning Graph Neural Network for Drug-Drug Interaction Event Prediction
Zhankun Xiong, Shichao Liu, Feng Huang, Ziyan Wang, Xuan Liu, Zhongfei Zhang, Wen Zhang
-
Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs
Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen
-
DHGE: Dual-View Hyper-Relational Knowledge Graph Embedding for Link Prediction and Entity Typing
Haoran Luo, Haihong E, Ling Tan, Gengxian Zhou, Tianyu Yao, Kaiyang Wan
-
Generalizing Downsampling from Regular Data to Graphs
Davide Bacciu, Alessio Conte, Francesco Landolfi
-
Learnable Spectral Wavelets on Dynamic Graphs to Capture Global Interactions
Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Toyotaro Suzumura, Manish Singh
-
FTM: A Frame-Level Timeline Modeling Method for Temporal Graph Representation Learning
Bowen Cao, Qichen Ye, Weiyuan Xu, Yuexian Zou
-
Where Will Players Move Next? Dynamic Graphs and Hierarchical Fusion for Movement Forecasting in Badminton
Kai-Shiang Chang, Wei-Yao Wang, Wen-Chih Peng
-
Graph Ordering Attention Networks
Michail Chatzianastasis, Johannes Lutzeyer, George Dasoulas, Michalis Vazirgiannis
-
Attribute and Structure Preserving Graph Contrastive Learning
Jialu Chen, Gang Kou
-
Context-Aware Safe Medication Recommendations with Molecular Graph and DDI Graph Embedding
Qianyu Chen, Xin Li, Kunnan Geng, Mingzhong Wang
-
Topological Pooling on Graphs
Yuzhou Chen, Yulia R. Gel
-
Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning
Jiashun Cheng, Man Li, Jia Li, Fugee Tsung
-
Scalable Spatiotemporal Graph Neural Networks
Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi
-
CrysGNN: Distilling Pre-trained Knowledge to Enhance Property Prediction for Crystalline Materials
Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung-Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly
-
Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning
Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu
-
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution
Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
-
Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View
Jingcan Duan, Siwei Wang, Pei Zhang, En Zhu, Jingtao Hu, Hu Jin, Yue Liu, Zhibin Dong
-
Directed Acyclic Graph Structure Learning from Dynamic Graphs
Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi
-
Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees
Zhongxi Fang, Jianming Huang, Xun Su, Hiroyuki Kasai
-
Scalable Attributed-Graph Subspace Clustering
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
-
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li
-
Interpolating Graph Pair to Regularize Graph Classification
Hongyu Guo, Yongyi Mao
-
Graph Knows Unknowns: Reformulate Zero-Shot Learning as Sample-Level Graph Recognition
Jingcai Guo, Song Guo, Qihua Zhou, Ziming Liu, Xiaocheng Lu, Fushuo Huo
-
Self-Supervised Bidirectional Learning for Graph Matching
Wenqi Guo, Lin Zhang, Shikui Tu, Lei Xu
-
Boosting Graph Neural Networks via Adaptive Knowledge Distillation
Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla
-
Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis
Thi Kieu Khanh Ho, Narges Armanfard
-
Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering
Zongmo Huang, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu, Lifang He
-
Multi-View MOOC Quality Evaluation via Information-Aware Graph Representation Learning
Lu Jiang, Yibin Wang, Jianan Wang, Pengyang Wang, Minghao Yin
-
Spatio-Temporal Meta-Graph Learning for Traffic Forecasting
Renhe Jiang, Zhaonan Wang, Jiawei Yong, Puneet Jeph, Quanjun Chen, Yasumasa Kobayashi, Xuan Song, Shintaro Fukushima, Toyotaro Suzumura
-
Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs
Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu
-
Local-Global Defense against Unsupervised Adversarial Attacks on Graphs
Di Jin, Bingdao Feng, Siqi Guo, Xiaobao Wang, Jianguo Wei, Zhen Wang
-
Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters
Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee
-
LoNe Sampler: Graph Node Embeddings by Coordinated Local Neighborhood Sampling
Konstantin Kutzkov
-
I’m Me, We’re Us, and I’m Us: Tri-directional Contrastive Learning on Hypergraphs
Dongjin Lee, Kijung Shin
-
Time-Aware Random Walk Diffusion to Improve Dynamic Graph Learning
Jong-whi Lee, Jinhong Jung
-
Differentiable Meta Multigraph Search with Partial Message Propagation on Heterogeneous Information Networks
Chao Li, Hao Xu, Kun He
-
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks
Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng
-
Restructuring Graph for Higher Homophily via Adaptive Spectral Clustering
Shouheng Li, Dongwoo Kim, Qing Wang
-
Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network
Tong Li, Jiale Deng, Yanyan Shen, Luyu Qiu, Huang Yongxiang, Caleb Chen Cao
-
Dual Label-Guided Graph Refinement for Multi-View Graph Clustering
Yawen Ling, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He
-
Hard Sample Aware Network for Contrastive Deep Graph Clustering
Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, Jingcan Duan, Cancan Chen
-
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach
Sérgio Machado, Anirudh Sridhar, Paulo Gil, Jorge Henriques, José M. F. Moura, Augusto Santos
-
Boundary Graph Neural Networks for 3D Simulations
Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter
-
Multiplex Graph Representation Learning via Common and Private Information Mining
Yujie Mo, Zongqian Wu, Yuhuan Chen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu
-
Inferring Patient Zero on Temporal Networks via Graph Neural Networks
Xiaolei Ru, Jack Murdoch Moore, Xin-Ya Zhang, Yeting Zeng, Gang Yan
-
Neighbor Contrastive Learning on Learnable Graph Augmentation
Xiao Shen, Dewang Sun, Shirui Pan, Xi Zhou, Laurence T. Yang
-
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing
Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang
-
Metric Multi-View Graph Clustering
Yuze Tan, Yixi Liu, Hongjie Wu, Jiancheng Lv, Shudong Huang
-
Heterogeneous Graph Masked Autoencoders
Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla
-
USER: Unsupervised Structural Entropy-Based Robust Graph Neural Network
Yifei Wang, Yupan Wang, Zeyu Zhang, Song Yang, Kaiqi Zhao, Jiamou Liu
-
FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability
Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, Cheng Wang
-
Non-IID Transfer Learning on Graphs
Jun Wu, Jingrui He, Elizabeth Ainsworth
-
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework
Lirong Wu, Haitao Lin, Yufei Huang, Tianyu Fan, Stan Z. Li
-
Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks
Yihan Wu, Aleksandar Bojchevski, Heng Huang
-
GraphPrompt: Graph-Based Prompt Templates for Biomedical Synonym Prediction
Hanwen Xu, Jiayou Zhang, Zhirui Wang, Shizhuo Zhang, Megh Bhalerao, Yucong Liu, Dawei Zhu, Sheng Wang
-
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis
Han Xuanyuan, Pietro Barbiero, Dobrik Georgiev, Lucie Charlotte Magister, Pietro Liò
-
Reinforcement Causal Structure Learning on Order Graph
Dezhi Yang, Guoxian Yu, Jun Wang, Zhengtian Wu, Maozu Guo
-
Simple and Efficient Heterogeneous Graph Neural Network
Xiaocheng Yang, Mingyu Yan, Shirui Pan, Xiaochun Ye, Dongrui Fan
-
Cluster-Guided Contrastive Graph Clustering Network
Xihong Yang, Yue Liu, Sihang Zhou, Siwei Wang, Wenxuan Tu, Qun Zheng, Xinwang Liu, Liming Fang, En Zhu
-
Lifelong Compression Mixture Model via Knowledge Relationship Graph
Fei Ye, Adrian G. Bors
-
Random Walk Conformer: Learning Graph Representation from Long and Short Range
Pei-Kai Yeh, Hsi-Wen Chen, Ming-Syan Chen
-
Priori Anchor Labels Supervised Scalable Multi-View Bipartite Graph Clustering
Jiali You, Zhenwen Ren, Xiaojian You, Haoran Li, Yuancheng Yao
-
Substructure Aware Graph Neural Networks
DingYi Zeng, Wanlong Liu, Wenyu Chen, Li Zhou, Malu Zhang, Hong Qu
-
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification
Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li
-
DRGCN: Dynamic Evolving Initial Residual for Deep Graph Convolutional Networks
Lei Zhang, Xiaodong Yan, Jianshan He, Ruopeng Li, Wei Chu
-
Let the Data Choose: Flexible and Diverse Anchor Graph Fusion for Scalable Multi-View Clustering
Pei Zhang, Siwei Wang, Liang Li, Changwang Zhang, Xinwang Liu, En Zhu, Zhe Liu, Lu Zhou, Lei Luo
-
Spectral Feature Augmentation for Graph Contrastive Learning and Beyond
Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King
-
Dynamic Heterogeneous Graph Attention Neural Architecture Search
Zeyang Zhang, Ziwei Zhang, Xin Wang, Yijian Qin, Zhou Qin, Wenwu Zhu
-
Tensorized Incomplete Multi-View Clustering with Intrinsic Graph Completion
Shuping Zhao, Jie Wen, Lunke Fei, Bob Zhang
-
Data Imputation with Iterative Graph Reconstruction
Jiajun Zhong, Ning Gui, Weiwei Ye
-
Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical Models
Jonathan Feldstein, Dominic Phillips, Efthymia Tsamoura
-
Fair Short Paths in Vertex-Colored Graphs
Matthias Bentert, Leon Kellerhals, Rolf Niedermeier
-
GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks
Angelina Brilliantova, Hannah Miller, Ivona Bezáková
-
Reviewing Labels: Label Graph Network with Top-k Prediction Set for Relation Extraction
Bo Li, Wei Ye, Jinglei Zhang, Shikun Zhang
-
Graph Component Contrastive Learning for Concept Relatedness Estimation
Yueen Ma, Zixing Song, Xuming Hu, Jingjing Li, Yifei Zhang, Irwin King
-
Improving Interpretability via Explicit Word Interaction Graph Layer
Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi
-
Exploring Faithful Rationale for Multi-Hop Fact Verification via Salience-Aware Graph Learning
Jiasheng Si, Yingjie Zhu, Deyu Zhou
-
Continual Graph Convolutional Network for Text Classification
Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding
-
Orders Are Unwanted: Dynamic Deep Graph Convolutional Network for Personality Detection
Tao Yang, Jinghao Deng, Xiaojun Quan, Qifan Wang
-
Towards Open Temporal Graph Neural Networks
Kaituo Feng, Changsheng Li, Xiaolu Zhang, JUN ZHOU
-
AutoGT: Automated Graph Transformer Architecture Search
Zizhao Zhang, Xin Wang, Chaoyu Guan, Ziwei Zhang, Haoyang Li, Wenwu Zhu
-
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
Bohang Zhang, Shengjie Luo, Liwei Wang, Di He
-
Graph Neural Networks for Link Prediction with Subgraph Sketching
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire
-
Do We Really Need Complicated Model Architectures For Temporal Networks?
Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
-
Learning on Large-scale Text-attributed Graphs via Variational Inference
Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang
-
Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks
Guangji Bai, Chen Ling, Liang Zhao
-
Learning Fair Graph Representations via Automated Data Augmentations
Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou
-
Spectral Augmentation for Self-Supervised Learning on Graphs
Lu Lin, Jinghui Chen, Hongning Wang
-
Serving Graph Compression for Graph Neural Networks
Si Si, Felix Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar
-
Effects of Graph Convolutions in Multi-layer Networks
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
-
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation
Xuheng Cai, Chao Huang, Lianghao Xia, Xubin Ren
-
Relational Attention: Generalizing Transformers for Graph-Structured Tasks
Cameron Diao, Ricky Loynd
-
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
Yi-Lun Liao, Tess Smidt
-
Learning rigid dynamics with face interaction graph networks
Kelsey R Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William F Whitney, Alvaro Sanchez-Gonzalez, Peter Battaglia, Tobias Pfaff
-
Relational Attention: Generalizing Transformers for Graph-Structured Tasks
Cameron Diao, Ricky Loynd
-
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
-
ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion
Aleksandar Pavlović, Emanuel Sallinger
-
Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency
Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh Chawla
-
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan
-
On Representing Linear Programs by Graph Neural Networks
Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin
-
ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin
-
MeshDiffusion: Score-based Generative 3D Mesh Modeling
Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu
-
LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence
Zhihao Shi, Xize Liang, Jie Wang
-
Learning Controllable Adaptive Simulation for Multi-resolution Physics
Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec
-
Automated Data Augmentations for Graph Classification
Youzhi Luo, Michael Curtis McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji
-
Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization
Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, Chuxu Zhang
-
Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective
Kuan Li, Yang Liu, Xiang Ao, Qing He
-
Agent-based Graph Neural Networks
Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer
-
Characterizing the Influence of Graph Elements
Zizhang Chen, Peizhao Li, Hongfu Liu, Pengyu Hong
-
Limitless Stability for Graph Convolutional Networks
Christian Koke
-
NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
Jinsong Chen, Kaiyuan Gao, Gaichao Li, Kun He
-
Empowering Graph Representation Learning with Test-Time Graph Transformation
Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
-
N-WL: A New Hierarchy of Expressivity for Graph Neural Networks
Qing Wang, Dillon Ze Chen, Asiri Wijesinghe, Shouheng Li, Muhammad Farhan
-
Are More Layers Beneficial to Graph Transformers?
Haiteng Zhao, Shuming Ma, Dongdong Zhang, Zhi-Hong Deng, Furu Wei
-
Strategic Classification with Graph Neural Networks
Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld
-
Robust Graph Dictionary Learning
Weijie Liu, Jiahao Xie, Chao Zhang, Makoto Yamada, Nenggan Zheng, Hui Qian
-
Specformer: Spectral Graph Neural Networks Meet Transformers
Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao
-
DiGress: Discrete Denoising diffusion for graph generation
Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard
-
LogicDP: Creating Labels for Graph Data via Inductive Logic Programming
Yuan Yang, Faramarz Fekri, James Clayton Kerce, Ali Payani
-
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning
Zehao Niu, Mihai Anitescu, Jie Chen
-
Explaining Temporal Graph Models through an Explorer-Navigator Framework
Wenwen Xia, Mincai Lai, Caihua Shan, Yao Zhang, Xinnan Dai, Xiang Li, Dongsheng Li
-
Learning Symbolic Models for Graph-structured Physical Mechanism
Hongzhi Shi, Jingtao Ding, Yufan Cao, quanming yao, Li Liu, Yong Li
-
Efficient Model Updates for Approximate Unlearning of Graph-Structured Data
Eli Chien, Chao Pan, Olgica Milenkovic
-
Imitating Graph-Based Planning with Goal-Conditioned Policies
Junsu Kim, Younggyo Seo, Sungsoo Ahn, Kyunghwan Son, Jinwoo Shin
-
MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning
Namyong Park, Ryan A. Rossi, Nesreen Ahmed, Christos Faloutsos
-
On Compositional Uncertainty Quantification for Seq2seq Graph Parsing
Zi Lin, Du Phan, Panupong Pasupat, Jeremiah Zhe Liu, Jingbo Shang
-
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang
-
Grounding Graph Network Simulators using Physical Sensor Observations
Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann
-
Graph Contrastive Learning for Skeleton-based Action Recognition
Xiaohu Huang, Hao Zhou, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang, Xinggang Wang, Wenyu Liu, Bin Feng
-
A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps
Kiarash Jamali, Dari Kimanius, Sjors HW Scheres
-
Energy-based Out-of-Distribution Detection for Graph Neural Networks
Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan
-
Rethinking Graph Lottery Tickets: Graph Sparsity Matters
Bo Hui, Da Yan, Xiaolong Ma, Wei-Shinn Ku
-
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems
Suresh Bishnoi, Ravinder Bhattoo, Jayadeva Jayadeva, Sayan Ranu, N M Anoop Krishnan
-
Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
Seungwoong Ha, Hawoong Jeong
-
GReTo: Remedying dynamic graph topology-task discordance via target homophily
Zhengyang Zhou, qihe huang, Gengyu Lin, Kuo Yang, LEI BAI, Yang Wang
-
Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks
Cheng Zhang
-
Unveiling the sampling density in non-uniform geometric graphs
Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie
-
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization
Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang
-
Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules
Jun Xia, Chengshuai Zhao, Bozhen Hu, Zhangyang Gao, Cheng Tan, Yue Liu, Siyuan Li, Stan Z. Li
-
Diffusion Models for Causal Discovery via Topological Ordering
Pedro Sanchez, Xiao Liu, Alison Q O'Neil, Sotirios A. Tsaftaris
-
Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning
Deyao Zhu, Li Erran Li, Mohamed Elhoseiny
-
FoSR: First-order spectral rewiring for addressing oversquashing in GNNs
Kedar Karhadkar, Pradeep Kr. Banerjee, Guido Montufar
-
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu
-
Revisiting Robustness in Graph Machine Learning
Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann
-
Learnable Graph Convolutional Attention Networks
Adrián Javaloy, Pablo Sanchez Martin, Amit Levi, Isabel Valera
-
Matching receptor to odorant with protein language and graph neural networks
Matej Hladiš, Maxence Lalis, Sebastien Fiorucci, Jérémie Topin
-
Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
Kai Xu, Georgi Ganev, Emile Joubert, Rees Davison, Olivier Van Acker, Luke Robinson
-
A critical look at the evaluation of GNNs under heterophily: Are we really making progress?
Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova
-
Fair Attribute Completion on Graph with Missing Attributes
Dongliang Guo, Zhixuan Chu, Sheng Li
-
Multimodal Analogical Reasoning over Knowledge Graphs
Ningyu Zhang, Lei Li, Xiang Chen, Xiaozhuan Liang, Shumin Deng, Huajun Chen
-
Global Explainability of GNNs via Logic Combination of Learned Concepts
Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Lio, Andrea Passerini
-
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks
Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik
-
A2Q: Aggregation-Aware Quantization for Graph Neural Networks
Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng
-
Graph Domain Adaptation via Theory-Grounded Spectral Regularization
Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
-
Learning Hierarchical Protein Representations via Complete 3D Graph Networks
Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji
-
Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States
Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin
-
Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation
Yun Young Choi, Sun Woo Park, Youngho Woo, U Jin Choi
-
A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
Xinyi Wu, Zhengdao Chen, William Wei Wang, Ali Jadbabaie
-
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
Alessio Gravina, Davide Bacciu, Claudio Gallicchio
-
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
Xiaoqi Wang, Han Wei Shen
-
Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
Bowen Jin, Yu Zhang, Yu Meng, Jiawei Han
-
Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs
Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron N Musco
-
Protein Representation Learning via Knowledge Enhanced Primary Structure Reasoning
Hong-Yu Zhou, Yunxiang Fu, Zhicheng Zhang, Bian Cheng, Yizhou Yu
-
Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems
Zhongyuan Zhao, Ananthram Swami, Santiago Segarra
-
Anisotropic Message Passing: Graph Neural Networks with Directional and Long-Range Interactions
Moritz Thürlemann, Sereina Riniker
-
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang
-
Confidence-Based Feature Imputation for Graphs with Partially Known Features
Daeho Um, Jiwoong Park, Seulki Park, Jin young Choi
-
Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves
-
Neural Compositional Rule Learning for Knowledge Graph Reasoning
Kewei Cheng, Nesreen Ahmed, Yizhou Sun
-
DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks
Wenqian Li, Yinchuan Li, Zhigang Li, Jianye HAO, Yan Pang
-
On Representing Mixed-Integer Linear Programs by Graph Neural Networks
Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin
-
UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph
Jinhao Jiang, Kun Zhou, Xin Zhao, Ji-Rong Wen
-
Boosting the Cycle Counting Power of Graph Neural Networks with I2-GNNs
Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang
-
AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks
Kaidi Cao, Jiaxuan You, Jiaju Liu, Jure Leskovec
-
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan
-
Subsampling in Large Graphs Using Ricci Curvature
Shushan Wu, Huimin Cheng, Jiazhang Cai, Ping Ma, Wenxuan Zhong
-
Spacetime Representation Learning
Marc T. Law, James Lucas
-
Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
Chi Han, Qizheng He, Charles Yu, Xinya Du, Hanghang Tong, Heng Ji
-
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah
-
A Message Passing Perspective on Learning Dynamics of Contrastive Learning
Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang
-
A Differential Geometric View and Explainability of GNN on Evolving Graphs
Yazheng Liu, Xi Zhang, Sihong Xie
-
Link Prediction with Non-Contrastive Learning
William Shiao, Zhichun Guo, Tong Zhao, Evangelos E. Papalexakis, Yozen Liu, Neil Shah
-
Learning to Induce Causal Structure
Nan Rosemary Ke, Silvia Chiappa, Jane X Wang, Jorg Bornschein, Anirudh Goyal, Melanie Rey, Theophane Weber, Matthew Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
-
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing
Yunchong Song, Chenghu Zhou, Xinbing Wang, Zhouhan Lin
-
Logical Message Passing Networks with One-hop Inference on Atomic Formulas
Zihao Wang, Yangqiu Song, Ginny Wong, Simon See
-
Fundamental Limits in Formal Verification of Message-Passing Neural Networks
Marco Sälzer, Martin Lange
-
Robust Scheduling with GFlowNets
David W Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan
-
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion
Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo
-
O-GNN: incorporating ring priors into molecular modeling
Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu
-
Molecule Generation For Target Protein Binding with Structural Motifs
ZAIXI ZHANG, Yaosen Min, Shuxin Zheng, Qi Liu
-
A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming
Qingyu Han, Linxin Yang, Qian Chen, Xiang Zhou, Dong Zhang, Akang Wang, Ruoyu Sun, Xiaodong Luo
-
Label Propagation with Weak Supervision
Rattana Pukdee, Dylan Sam, Pradeep Kumar Ravikumar, Nina Balcan
-
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond
Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang
-
Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem
Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi S. Jaakkola
-
On Explaining Neural Network Robustness with Activation Path
Ziping Jiang
-
Equivariant Hypergraph Diffusion Neural Operators
Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
-
Interpretable Geometric Deep Learning via Learnable Randomness Injection
Siqi Miao, Yunan Luo, Mia Liu, Pan Li
-
Protein Representation Learning by Geometric Structure Pretraining
Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang
-
Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction
Daehee Park, Hobin Ryu, Yunseo Yang, Jegyeong Cho, Jiwon Kim, Kuk-Jin Yoon
-
TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs
Siheng Xiong, Yuan Yang, Faramarz Fekri, James Clayton Kerce
-
Boosting Causal Discovery via Adaptive Sample Reweighting
An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua
-
BLADE: Biased Neighborhood Sampling based Graph Neural Network for Directed Graphs
Srinivas Virinchi, Anoop Saladi
-
Simplifying Graph-based Collaborative Filtering for Recommendation
Li He, Xianzhi Wang, Dingxian Wang, Haoyuan Zou, Hongzhi Yin, Guandong Xu
-
Self-Supervised Group Graph Collaborative Filtering for Group Recommendation
Kang Li, Chang-Dong Wang, Jian-Huang Lai, Huaqiang Yuan
-
Minimum Entropy Principle Guided Graph Neural Networks
Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Hao Peng, Angsheng Li, Shan Xue, Jianlin Su
-
Learning to Distill Graph Neural Networks
Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin
-
MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution
Wendong Bi, Lun Du, Qiang Fu, Yanlin Wang, Shi Han, Dongmei Zhang
-
Global Counterfactual Explainer for Graph Neural Networks
Zexi Huang, Mert Kosan, Sourav Medya, Sayan Ranu, Ambuj K. Singh
-
Effective Graph Kernels for Evolving Functional Brain Networks
Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu
-
Self-Supervised Graph Structure Refinement for Graph Neural Networks
Jianan Zhao, Qianlong Wen, Mingxuan Ju, Chuxu Zhang, Yanfang Ye
-
Learning Stance Embeddings from Signed Social Graphs
John Pougué-Biyong, Akshay Gupta, Aria Haghighi, Ahmed El-Kishky
-
Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation
Xiaoyu Zhang, Xin Xin, Dongdong Li, Wenxuan Liu, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren
-
A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework
Xu Wang, Lianliang Chen, Hongbo Zhang, Pengkun Wang, Zhengyang Zhou, Yang Wang
-
Simultaneous Linear Multi-view Attributed Graph Representation Learning and Clustering
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
-
Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs
Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang
-
Self-supervised Graph Representation Learning for Black Market Account Detection
Zequan Xu, Lianyun Li, Hui Li, Qihang Sun, Shaofeng Hu, Rongrong Ji
-
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan
-
Alleviating Structural Distribution Shift in Graph Anomaly Detection
Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang
-
Cognition-aware Knowledge Graph Reasoning for Explainable Recommendation
Qingyu Bing, Qiannan Zhu, Zhicheng Dou
-
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation
Yifang Qin, Yifan Wang, Fang Sun, Wei Ju, Xuyang Hou, Zhe Wang, Jia Cheng, Jun Lei, Ming Zhang
-
VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation
Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu, Han Xu
-
Heterogeneous Graph Contrastive Learning for Recommendation
Mengru Chen, Chao Huang, Lianghao Xia, Wei Wei, Yong Xu, Ronghua Luo
-
SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation
Boyu Li, Ting Guo, Xingquan Zhu, Qian Li, Yang Wang, Fang Chen
-
Robust Training of Graph Neural Networks via Noise Governance
Siyi Qian, Haochao Ying, Renjun Hu, Jingbo Zhou, Jintai Chen, Danny Z. Chen, Jian Wu
-
Cooperative Explanations of Graph Neural Networks
Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua
-
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection
Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
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Towards Faithful and Consistent Explanations for Graph Neural Networks
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
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Position-Aware Subgraph Neural Networks with Data-Efficient Learning
Chang Liu, Yuwen Yang, Zhe Xie, Hongtao Lu, Yue Ding
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Graph Neural Networks with Interlayer Feature Representation for Image Super-Resolution
Shenggui Tang, Kaixuan Yao, Jianqing Liang, Zhiqiang Wang, Jiye Liang
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DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation
Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang
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Inductive Graph Transformer for Delivery Time Estimation
Xin Zhou, Jinglong Wang, Yong Liu, Xingyu Wu, Zhiqi Shen, Cyril Leung
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Search Behavior Prediction: A Hypergraph Perspective
Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian
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Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation
Zhen Tian, Ting Bai, Zibin Zhang, Zhiyuan Xu, Kangyi Lin, Ji-Rong Wen, Wayne Xin Zhao
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Heterogeneous Graph-based Context-aware Document Ranking
Shuting Wang, Zhicheng Dou, Yutao Zhu
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Graph Summarization via Node Grouping: A Spectral Algorithm
Arpit Merchant, Michael Mathioudakis, Yanhao Wang
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Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph
Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu
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Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs
Linhao Luo, Gholamreza Haffari, Shirui Pan
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S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking
Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu
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Combining vs. Transferring Knowledge: Investigating Strategies for Improving Demographic Inference in Low Resource Settings
Yaguang Liu, Lisa Singh
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Active Ensemble Learning for Knowledge Graph Error Detection
Junnan Dong, Qinggang Zhang, Xiao Huang, Qiaoyu Tan, Daochen Zha, Zihao Zhao
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Stochastic Solutions for Dense Subgraph Discovery in Multilayer Networks
Yasushi Kawase, Atsushi Miyauchi, Hanna Sumita
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Modeling Fine-grained Information via Knowledge-aware Hierarchical Graph for Zero-shot Entity Retrieval
Taiqiang Wu, Xingyu Bai, Weigang Guo, Weijie Liu, Siheng Li, Yujiu Yang
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Web of Conferences: A Conference Knowledge Graph
Shuo Yu, Ciyuan Peng, Chengchuan Xu, Chen Zhang, Feng Xia
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Developing and Evaluating Graph Counterfactual Explanation with GRETEL
Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
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Generalizing Graph Neural Network across Graphs and Time
Zhihao Wen
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Graphs: Privacy and Generation through ML
Rucha Bhalchandra Joshi
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Data-Efficient Graph Learning Meets Ethical Challenges
Tao Tang
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From Classic GNNs to Hyper-GNNs for Detecting Camouflaged Malicious Actors
Venus Haghighi
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Efficient Graph Learning for Anomaly Detection Systems
Falih Gozi Febrinanto
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GELTOR: A Graph Embedding Method based on Listwise Learning to Rank
Masoud Reyhani Hamedani, Jin-Su Ryu, Sang-Wook Kim
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Graph-less Collaborative Filtering
Lianghao Xia, Chao Huang, Jiao Shi, Yong Xu
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Fair Graph Representation Learning via Diverse Mixture-of-Experts
Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang
-
Multi-Aspect Heterogeneous Graph Augmentation
Yuchen Zhou, Yanan Cao, Yongchao Liu, Yanmin Shang, Peng Zhang, Zheng Lin, Yun Yue, Baokun Wang, Xing Fu, Weiqiang Wang
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RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks
Zeyu Zhang, Jiamou Liu, Xianda Zheng, Yifei Wang, Pengqian Han, Yupan Wang, Kaiqi Zhao, Zijian Zhang
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Collaboration-Aware Graph Convolutional Network for Recommender Systems
Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr
-
Hierarchical Knowledge Graph Learning Enabled Socioeconomic Indicator Prediction in Location-Based Social Network
Zhilun Zhou, Yu Liu, Jingtao Ding, Depeng Jin, Yong Li
-
SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking
Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
-
Graph Self-supervised Learning with Augmentation-aware Contrastive Learning
Dong Chen, Xiang Zhao, Wei Wang, Zhen Tan, Weidong Xiao
-
Enhancing Hierarchy-Aware Graph Networks with Deep Dual Clustering for Session-based Recommendation
Jiajie Su, Chaochao Chen, Weiming Liu, Fei Wu, Xiaolin Zheng, Haoming Lyu
-
Unifying and Improving Graph Convolutional Neural Networks with Wavelet Denoising Filters
Liangtian Wan, Xiaona Li, Huijin Han, Xiaoran Yan, Lu Sun, Zhaolong Ning, Feng Xia
-
SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds
Junda Ye, Zhongbao Zhang, Li Sun, Yang Yan, Feiyang Wang, Fuxin Ren
-
GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks
Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang
-
An Attentional Multi-scale Co-evolving Model for Dynamic Link Prediction
Guozhen Zhang, Tian Ye, Depeng Jin, Yong Li
-
Robust Graph Representation Learning for Local Corruption Recovery
Bingxin Zhou, Yuanhong Jiang, Yuguang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang
-
Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation
Zhongxuan Han, Xiaolin Zheng, Chaochao Chen, Wenjie Cheng, Yang Yao
-
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification
Xingcheng Fu, Yuecen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li
-
Graph Neural Networks without Propagation
Liang Yang, Qiuliang Zhang, Runjie Shi, Wenmiao Zhou, Bingxin Niu, Chuan Wang, Xiaochun Cao, Dongxiao He, Zhen Wang, Yuanfang Guo
-
TIGER: Temporal Interaction Graph Embedding with Restarts
Yao Zhang, Yun Xiong, Yongxiang Liao, Yiheng Sun, Yucheng Jin, Xuehao Zheng, Yangyong Zhu
-
Self-Supervised Teaching and Learning of Representations on Graphs
Liangtian Wan, Zhenqiang Fu, Lu Sun, Xianpeng Wang, Gang Xu, Xiaoran Yan, Feng Xia
-
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization
Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu
-
Homophily-oriented Heterogeneous Graph Rewiring
Jiayan Guo, Lun Du, Wendong Bi, Qiang Fu, Xiaojun Ma, Xu Chen, Shi Han, Dongmei Zhang, Yan Zhang
-
HGWaveNet: A Hyperbolic Graph Neural Network for Temporal Link Prediction
Qijie Bai, Changli Nie, Haiwei Zhang, Dongming Zhao, Xiaojie Yuan
-
Rethinking Structural Encodings: Adaptive Graph Transformer for Node Classification Task
Xiaojun Ma, Qin Chen, Yi Wu, Guojie Song, Liang Wang, Bo Zheng
-
CMINet: a Graph Learning Framework for Content-aware Multi-channel Influence Diffusion
Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen
-
Federated Node Classification over Graphs with Latent Link-type Heterogeneity
Han Xie, Li Xiong, Carl Yang
-
Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs
Susheel Suresh, Mayank Shrivastava, Arko Mukherjee, Jennifer Neville, Pan Li
-
Semi-Supervised Embedding of Attributed Multiplex Networks
Ylli Sadikaj, Justus Rass, Yllka Velaj, Claudia Plant
-
Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification
Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao
-
HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer
Qiheng Mao, Zemin Liu, Chenghao Liu, Jianling Sun
-
Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs
Xin Zheng, Miao Zhang, Chunyang Chen, Qin Zhang, Chuan Zhou, Shirui Pan
-
Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning
Haoran Yang, Hongxu Chen, Sixiao Zhang, Xiangguo Sun, Qian Li, Xiangyu Zhao, Guandong Xu
-
Minimum Topology Attacks for Graph Neural Networks
Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du
-
Multi-head Variational Graph Autoencoder Constrained by Sum-product Networks
Riting Xia, Yan Zhang, Chunxu Zhang, Xueyan Liu, Bo Yang
-
GIF: A General Graph Unlearning Strategy via Influence Function
Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He
-
INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging
Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, Jianzhong Qi, Chaochao Chen, Longbiao Chen
-
Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation
Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin, Shirui Pan
-
Toward Degree Bias in Embedding-Based Knowledge Graph Completion
Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang
-
Unlearning Graph Classifiers with Limited Data Resources
Chao Pan, Eli Chien, Olgica Milenkovic
-
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks
Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu
-
GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner
Zhenyu Hou, Yufei He, Yukuo Cen, Xiao Liu, Yuxiao Dong, Evgeny Kharlamov, Jie Tang
-
CogDL: A Comprehensive Library for Graph Deep Learning
Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Zhongming Yu, Hengrui Zhang, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Yuxiao Dong, Yang Yang, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang
-
ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation
Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, Jie Tang
-
Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model
Xiaoyu You, Chi Li, Daizong Ding, Mi Zhang, Fuli Feng, Xudong Pan, Min Yang
-
Compressed Interaction Graph based Framework for Multi-behavior Recommendation
Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang
-
Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation
Zixuan Xu, Penghui Wei, Shaoguo Liu, Weimin Zhang, Liang Wang, Bo Zheng
-
Robust Preference-Guided Denoising for Graph based Social Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin, Yong Li
-
Multi-Behavior Recommendation with Cascading Graph Convolution Networks
Zhiyong Cheng, Sai Han, Fan Liu, Lei Zhu, Zan Gao, Yuxin Peng
-
Personalized Graph Signal Processing for Collaborative Filtering
Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu
-
Dynamically Expandable Graph Convolution for Streaming Recommendation
Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma
-
Dual Policy Learning for Aggregation Optimization in Graph Neural Network-based Recommender Systems
Heesoo Jung, Sangpil Kim, Hogun Park
-
Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum
Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang
-
Node-wise Diffusion for Scalable Graph Learning
Keke Huang, Jing Tang, Juncheng Liu, Renchi Yang, Xiaokui Xiao
-
CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization
Zheheng Luo, Qianqian Xie, Sophia Ananiadou
-
MaSS: Model-agnostic, Semantic and Stealthy Data Poisoning Attack on Knowledge Graph Embedding
Xiaoyu You, Beina Sheng, Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Fuli Feng
-
Curriculum Graph Poisoning
Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu, Yadong Mu
-
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification
Haozhen Zhang, Le Yu, Xi Xiao, Qing Li, Francesco Mercaldo, Xiapu Luo, Qixu Liu
-
Unnoticeable Backdoor Attacks on Graph Neural Networks
Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang
-
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding
Yuke Hu, Wei Liang, Ruofan Wu, Kai Xiao, Weiqiang Wang, Xiaochen Li, Jinfei Liu, Zhan Qin
-
Event Prediction using Case-Based Reasoning over Knowledge Graphs
Sola Shirai, Debarun Bhattacharjya, Oktie Hassanzadeh
-
Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning
Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, Liang Wang
-
Meta-Learning Based Knowledge Extrapolation for Temporal Knowledge Graph
Zhongwu Chen, Chengjin Xu, Fenglong Su, Zhen Huang, Yong Dou
-
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning
Xiangrong Zhu, Guangyao Li, Wei Hu
-
Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods
Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Johannes Hoffart, Manish Singh, Toyotaro Suzumura
-
Knowledge Graph Question Answering with Ambiguous Query
Lihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang, Hanghang Tong
-
Attribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignment
Qian Li, Shu Guo, Yangyifei Luo, Cheng Ji, Lihong Wang, Jiawei Sheng, Jianxin Li
-
Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs
Junnan Dong, Qinggang Zhang, Xiao Huang, Keyu Duan, Qiaoyu Tan, Zhimeng Jiang
-
Unsupervised Entity Alignment for Temporal Knowledge Graphs
Xiaoze Liu, Junyang Wu, Tianyi Li, Lu Chen, Yunjun Gao
-
Hierarchical Self-Attention Embedding for Temporal Knowledge Graph Completion
Xin Ren, Luyi Bai, Qianwen Xiao, Xiangxi Meng
-
KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion
Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo
-
TRAVERS: A Diversity-Based Dynamic Approach to Iterative Relevance Search over Knowledge Graphs
Ziyang Li, Yu Gu, Yulin Shen, Wei Hu, Gong Cheng
-
Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer
Wen Zhang, Yushan Zhu, Mingyang Chen, Yuxia Geng, Yufeng Huang, Yajing Xu, Wenting Song, Huajun Chen
-
TEA: Time-aware Entity Alignment in Knowledge Graphs
Yu Liu, Wen Hua, Kexuan Xin, Saeid Hosseini, Xiaofang Zhou
-
Link Prediction with Attention Applied on Multiple Knowledge Graph Embedding Models
Cosimo Gregucci, Mojtaba Nayyeri, Daniel Hernández, Steffen Staab
-
Knowledge Graph Completion with Counterfactual Augmentation
Heng Chang, Jie Cai, Jia Li
-
Mutually-paced Knowledge Distillation for Cross-lingual Temporal Knowledge Graph Reasoning
Ruijie Wang, Zheng Li, Jingfeng Yang, Tianyu Cao, Chao Zhang, Bing Yin, Tarek F. Abdelzaher
-
Message Function Search for Knowledge Graph Embedding
Shimin Di, Lei Chen
-
Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks
Yue Hu, Yuhang Zhang, Yanbing Wang, Daniel B. Work
-
Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space
Yankai Chen, Yixiang Fang, Yifei Zhang, Irwin King
-
Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs
Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd, Jingrui He
-
PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction
Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun
-
Learning to Simulate Crowd Trajectories with Graph Networks
Hongzhi Shi, Quanming Yao, Yong Li
-
Instant Representation Learning for Recommendation over Large Dynamic Graphs
Cheng Wu (Tsinghua University); Chaokun Wang (Tsinghua University); Jingcao Xu (Tsinghua University); ZiWei Fang (Tsinghua University); Tiankai Gu (Alibaba Group); Changping Wang (Kuai shou); Yang Song (Kuaishou Inc); Kai Zheng (Kuaishou); Xiaowei Wang (Beijing Kuaishou Technology Co., Ltd.); Guorui Zhou (Kuaishou Inc)*
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MMKGR: Multi-hop Multi-modal Knowledge Graph Reasoning
Shangfei Zheng (Soochow University); Weiqing Wang (Monash University); JIanfeng Qu (Soochow University); Hongzhi Yin (The University of Queensland); Wei Chen (Soochow University); Lei Zhao (Soochow University)*
-
Relational Temporal Graph Convolutional Networks for Ranking-Based Stock Prediction
Zetao Zheng (University of Electronic Science and Technology of China); Jie Shao (University of Electronic Science and Technology of China); Jia Zhu (Zhejiang Normal University); Heng Tao Shen (University of Electronic Science and Technology of China (UESTC))*
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TDB: Breaking All Hop-Constrained Cycles in Billion-Scale Directed Graphs
You Peng (University of New South Wales); Xuemin Lin (University of New South Wales); Michael R Yu (UNSW); Wenjie Zhang (University of New South Wales); Lu Qin (UTS)*
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Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction
Yufeng Zhang (Soochow University); Weiqing Wang (Monash University); Hongzhi Yin (The University of Queensland); Pengpeng Zhao (Soochow University); Wei Chen (Soochow University); Lei Zhao (Soochow University)*
-
When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks
Yuchen Fang (Beijing University of Posts and Telecommunications); Yanjun Qin (Beijing University of Posts and Telecommunications); Haiyong Luo (Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, Chinese Academy of Sciences); Fang Zhao (School of Software Engineering, Beijing University of Posts and Telecommunications); Bingbing Xu ( Institute of Computing Technology,University of Chinese Academy of Sciences); Liang Zeng (Tsinghua University); Chenxing Wang (Beijing University of Posts and Telecommunications)*
-
Jointly Attacking Graph Neural Network and its Explanations
“Wenqi FAN (The Hong Kong Polytechnic University); Han Xu (Michigan State University); Wei Jin (Michigan State University); Xiaorui Liu (North Carolina State University); Xianfeng Tang (Amazon); Suhang Wang (Pennsylvania State University); Qing Li (The Hong Kong Polytechnic University); Jiliang Tang (Michigan State University); Jianping Wang (City University of Hong Kong); Charu Aggarwal (IBM)”*
-
Revisiting Citation Prediction with Cluster-Aware Text-Enhanced Heterogeneous Graph Neural Networks
Carl Yang (Emory University); Jiawei Han (UIUC)*
-
CLDG: Contrastive Learning on Dynamic Graphs
Yiming Xu (Xi’an Jiaotong University); Bin Shi (Xi’an jiaotong University); Teng Ma (Xi’an Jiaotong University); Bo Dong (Xi’an Jiaotong University); Haoyi Zhou (Beihang University); Qinghua Zheng (School of Electronic and Information Engineering, Xi’an Jiaotong University)*
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Relational Message Passing for Fully Inductive Knowledge Graph Completion
Yuxia Geng (Zhejiang University); Jiaoyan Chen (The University of Manchester); Jeff Z. Pan (The University of Edinburgh); Mingyang Chen (Zhejiang University); Song Jiang (Huawei Technologies Co., Ltd); Wen Zhang (Zhejiang University); Huajun Chen (Zhejiang University)*
-
Layer-refined Graph Convolutional Networks for Recommendation
Xin Zhou (Nanyang Technological University); Donghui Lin (Okayama University); Yong Liu (Nanyang Technological University); Chunyan Miao (NTU)*
-
A Generic Reinforced Explainable Framework with Knowledge Graph for Session-based Recommendation
Huizi Wu (Shanghai University of Finance and Economics); Hui Fang (Shanghai University of Finance and Economics); Zhu Sun (ASTAR); Cong Geng (Shanghai University of Finance and Economics); Xinyu Kong (Ant Group); Yew Soon Ong (Nanyang Technological University, Nanyang View, Singapore)
-
HyGNN: Drug-Drug Interaction Prediction via Hypergraph Neural Network
Khaled Mohammed Saifuddin (Georgia State University); Briana Bumgardner (Rice University); Farhan Tanvir (Oklahoma State University); Esra Akbas (Georgia State University)*
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Demystifying Bitcoin Address Behavior via Graph Neural Networks
Zhengjie Huang (Zhejiang University); Yunyang Huang (UESTC); Peng Qian (Zhejiang University); Jianhai Chen (Zhejiang University); Qinming He (Zhejiang University)*
-
RETIA: Relation-Entity Twin-Interact Aggregation for Temporal Knowledge Graph Extrapolation
Kangzheng Liu (Huazhong University of Science and Technology); Feng Zhao (Huazhong University of Science and Technology); Guandong Xu (University of Technology Sydney, Australia); Xianzhi Wang (University of Technology Sydney); Hai Jin (Huazhong University of Science and Technology)*
-
Air-Ground Spatial Crowdsourcing with UAV Carriers by Geometric Graph Convolutional Multi-Agent Deep Reinforcement Learning
Yu Wang (Beijing Institute of Technology); Jingfei Wu (Beijing Institute of Technology); Hua Xingyuan (School of Computer Science Beijing Institute of Technology); Chi Harold Liu (Beijing Institute of Technology); Guozheng Li (Beijing Institute of Technology); Jianxin Zhao (Beijing Institute of Technology); Ye Yuan ( Beijing Institute of Technology); Guoren Wang (Beijing Institute of Technology)*
-
Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting
Yusheng Zhao (Peking University); Xiao Luo (UCLA); Wei Ju (Peking University); Chong Chen (Peking University); Xian-Sheng Hua (Terminus Group); Ming Zhang (Peking University)*
-
Disentangled Graph Social Recommendation
Lianghao Xia (University of Hong Kong); Yizhen Shao (South China University of Technology); Chao Huang (University of Hong Kong); Yong Xu (South China University of Technology); Huance Xu (South China University of Technology); Jian Pei (Simon Fraser University)*
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Fast Unsupervised Graph Embedding via Graph Zoom Learning
Ziyang Liu (Tsinghua University); Chaokun Wang (Tsinghua University); Yunkai Lou (Tsinghua University); Hao Feng (Tsinghua University)*
-
AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network
Guanghui Zhu (Nanjing University); zhu zhennan (Nanjing University); Wenjie Wang (Nanjing University); Zhuoer Xu (Nanjing University); Chunfeng Yuan (Nanjing University); Yihua Huang (Nanjing University)*
-
Multimodal Biological Knowledge Graph Completion via Triple Co-attention Mechanism
Derong Xu (University of Science and Technology of China); jingbo zhou (Baidu Research); Tong Xu (University of Science and Technology of China); yuan xia (baidu); Ji Liu (Baidu Research); Enhong Chen (University of Science and Technology of China); Dejing Dou (Baidu)*
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SEIGN: A Simple and Efficient Graph Neural Network for Large Dynamic Graphs
Xiao Qin (AWS AI/ML); Nasrullah Sheikh (IBM); Chuan Lei (Amazon Web Services); Berthold Reinwald (IBM Research-Almaden); Giacomo Domeniconi (U.S. Bank)*
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Spatio-Temporal Denoising Graph Autoencoders with Data Augmentation for Photovoltaic Data Imputation
Yangxin Fan (Case Western Reserve University); Xuanji Yu (Case Western Reserve University); Raymond Wieser (Case Western Reserve University); David Meakin (SunPower Corporation); Avishai Shaton (SolarEdge Technologies); Jean-Nicolas Jaubert (CSI Solar Co.Ltd.); Robert Flottemesch (Brookfield Renewable U.S.); Michael Howell (C2 Energy Capital); Jennifer Braid (Sandia National Labs); Laura Bruckman (Case Western Reserve University); Roger H French (Case Western Reserve University); Yinghui Wu (Case Western Reserve University)*
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Caerus: A Caching-based Framework for Scalable Temporal Graph Neural Networks
Yiming Li (Hong Kong University of Science and Technology); Yanyan Shen (Shanghai Jiao Tong University); Lei Chen (Hong Kong University of Science and Technology); Mingxuan Yuan (Huawei)*
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Scalable and Efficient Full-Graph GNN Training for Large Graphs
Xinchen Wan (HKUST); Kaiqiang Xu (HKUST); Xudong Liao (HKUST); Yilun Jin (The Hong Kong University of Science and Technology); Kai Chen (HKUST); Xin Jin (Peking University)
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EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs
Haoyang Li (The Hong Kong University of Science and Technology); Lei Chen (Hong Kong University of Science and Technology);
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DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with GPU
Xin Zhang (Hong Kong University of Science and Technology); Yanyan Shen (Shanghai Jiao Tong University); Yingxia Shao (BUPT); Lei Chen (Hong Kong University of Science and Technology)