Hypergraph Neural Networks (AAAI 2019)

Python package for hypergraph analysis and visualization.

KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.

[NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

Hypergraph is data structure library to create a directed hypergraph in which a hyperedge can join any number of vertices.

A curated list of Hypergraph Learning, Hypergraph Theory, Hypergraph Dataset and Hypergraph Tool.

C++/Wolfram Language package for exploring set and graph rewriting systems

NeurIPS 2019: HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs

Mt-KaHyPar (Multi-Threaded Karlsruhe Hypergraph Partitioner) is a shared-memory multilevel graph and hypergraph partitioner equipped with parallel implementations of techniques used in the best sequential partitioning algorithms. Mt-KaHyPar can partition extremely large hypergraphs very fast and with high quality.

Implementation of EMNLP2020 -- Be More with Less: Hypergraph Attention Networks for Inductive Text Classification

HypergraphZ - A Hypergraph Implementation in Zig

single-cell Hi-C, scHi-C, Hi-C, 3D genome, nuclear organization, hypergraph

The source code of IEEE TPAMI 2025 "Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation".

A performant, parallel, probabilistic, random acyclic-graph, low-latency, perfect hash generation library.

Collection of papers relating data-driven higher-order graph/networks researches.

Hypergraph Rewriting System

[NeurIPS'21] Higher-order Transformers for sets, graphs, and hypergraphs, in PyTorch

Code of the paper "Game theoretic hypergraph matching for multi-source image correspondences". [论文代码] 超图匹配和多源图像特征点匹配。

[WWW'21] Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks

Code for Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting