- Online Continual Learning in Image Classification: An Empirical Survey (arXiv 2020) [paper] [code]
- Continual Lifelong Learning in Natural Language Processing: A Survey (COLING 2020) [paper]
- Class-incremental learning: survey and performance evaluation (arXiv 2020) [paper] [code]
- A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks (Neural Networks) [paper] [code]
- A continual learning survey: Defying forgetting in classification tasks (TPAMI 2021) [paper] [arxiv]
- Continual Lifelong Learning with Neural Networks: A Review (Neural Networks) [paper]
- Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks (NAACL, 2021) [paper]
- Continual Learning for Text Classification with Information Disentanglement Based Regularization (NAACL, 2021) [paper]
- Layerwise Optimization by Gradient Decomposition for Continual Learning (CVPR, 2021) [paper]
- Adaptive Aggregation Networks for Class-Incremental Learning (CVPR, 2021) [paper]
- Incremental Few-Shot Instance Segmentation (CVPR, 2021) [paper]
- Efficient Feature Transformations for Discriminative and Generative Continual Learning (CVPR, 2021) [paper]
- On Learning the Geodesic Path for Incremental Learning (CVPR, 2021) [paper]
- Few-Shot Incremental Learning with Continually Evolved Classifiers (CVPR, 2021) [paper]
- Rectification-based Knowledge Retention for Continual Learning (CVPR, 2021) [paper]
- DER: Dynamically Expandable Representation for Class Incremental Learning (CVPR, 2021) [paper]
- Rainbow Memory: Continual Learning with a Memory of Diverse Samples (CVPR, 2021) [paper]
- Training Networks in Null Space of Feature Covariance for Continual Learning (CVPR, 2021) [paper]
- Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning (CVPR, 2021) [paper]
- PLOP: Learning without Forgetting for Continual Semantic Segmentation (CVPR, 2021) [paper]
- Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations (CVPR, 2021) [paper]
- Online Class-Incremental Continual Learning with Adversarial Shapley Value(AAAI, 2021) [paper] [code]
- Lifelong and Continual Learning Dialogue Systems: Learning during Conversation(AAAI, 2021) [paper]
- Continual learning for named entity recognition(AAAI, 2021) [paper]
- Using Hindsight to Anchor Past Knowledge in Continual Learning(AAAI, 2021) [paper]
- Curriculum-Meta Learning for Order-Robust Continual Relation Extraction(AAAI, 2021) [paper]
- Continual Learning by Using Information of Each Class Holistically(AAAI, 2021) [paper]
- Gradient Regularized Contrastive Learning for Continual Domain Adaptation(AAAI, 2021) [paper]
- Unsupervised Model Adaptation for Continual Semantic Segmentation(AAAI, 2021) [paper]
- A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation(AAAI, 2021) [paper]
- Do Not Forget to Attend to Uncertainty While Mitigating Catastrophic Forgetting(WACV, 2021) [paper]
- Continual Learning for Natural Language Generation in Task-oriented Dialog Systems(EMNLP, 2020) [paper]
- Distill and Replay for Continual Language Learning(COLING, 2020) [paper]
- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks (NeurIPS2020) [paper] [code]
- Meta-Consolidation for Continual Learning (NeurIPS2020) [paper]
- Understanding the Role of Training Regimes in Continual Learning (NeurIPS2020) [paper]
- Continual Learning with Node-Importance based Adaptive Group Sparse Regularization (NeurIPS2020) [paper]
- Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning (NeurIPS2020) [paper]
- Coresets via Bilevel Optimization for Continual Learning and Streaming (NeurIPS2020) [paper]
- RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning (NeurIPS2020) [paper]
- Continual Deep Learning by Functional Regularisation of Memorable Past (NeurIPS2020) [paper]
- Dark Experience for General Continual Learning: a Strong, Simple Baseline (NeurIPS2020) [paper] [code]
- GAN Memory with No Forgetting (NeurIPS2020) [paper]
- Calibrating CNNs for Lifelong Learning (NeurIPS2020) [paper]
- ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation(RecSys, 2020) [paper]
- Initial Classifier Weights Replay for Memoryless Class Incremental Learning (BMVC2020) [paper]
- Adversarial Continual Learning (ECCV2020) [paper] [code]
- REMIND Your Neural Network to Prevent Catastrophic Forgetting (ECCV2020) [paper] [code]
- Incremental Meta-Learning via Indirect Discriminant Alignment (ECCV2020) [paper]
- Memory-Efficient Incremental Learning Through Feature Adaptation (ECCV2020) [paper]
- PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning (ECCV2020) [paper] [code]
- Reparameterizing Convolutions for Incremental Multi-Task Learning Without Task Interference (ECCV2020) [paper]
- Learning latent representions across multiple data domains using Lifelong VAEGAN (ECCV2020) [paper]
- Online Continual Learning under Extreme Memory Constraints (ECCV2020) [paper]
- Class-Incremental Domain Adaptation (ECCV2020) [paper]
- More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning (ECCV2020) [paper]
- Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation (ECCV2020) [paper]
- GDumb: A Simple Approach that Questions Our Progress in Continual Learning (ECCV2020) [paper]
- Imbalanced Continual Learning with Partitioning Reservoir Sampling (ECCV2020) [paper]
- Topology-Preserving Class-Incremental Learning (ECCV2020) [paper]
- GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems (CIKM2020) [paper]
- OvA-INN: Continual Learning with Invertible Neural Networks (IJCNN2020) [paper]
- XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning (ICLM2020) [paper]
- Optimal Continual Learning has Perfect Memory and is NP-HARD (ICML2020) [paper]
- Neural Topic Modeling with Continual Lifelong Learning (ICML2020) [paper]
- Continual Learning with Knowledge Transfer for Sentiment Classification (ECML-PKDD2020) [paper] [code]
- Semantic Drift Compensation for Class-Incremental Learning (CVPR2020) [paper] [code]
- Few-Shot Class-Incremental Learning (CVPR2020) [paper]
- Modeling the Background for Incremental Learning in Semantic Segmentation (CVPR2020) [paper]
- Incremental Few-Shot Object Detection (CVPR2020) [paper]
- Incremental Learning In Online Scenario (CVPR2020) [paper]
- Maintaining Discrimination and Fairness in Class Incremental Learning (CVPR2020) [paper]
- Conditional Channel Gated Networks for Task-Aware Continual Learning (CVPR2020) [paper]
- Continual Learning with Extended Kronecker-factored Approximate Curvature (CVPR2020) [paper]
- iTAML : An Incremental Task-Agnostic Meta-learning Approach (CVPR2020) [paper] [code]
- Mnemonics Training: Multi-Class Incremental Learning without Forgetting (CVPR2020) [paper] [code]
- ScaIL: Classifier Weights Scaling for Class Incremental Learning (WACV2020) [paper]
- Accepted papers(ICLR2020) [paper]
- Brain-inspired replay for continual learning with artificial neural networks (Natrue Communications 2020) [paper] [code]
- Compacting, Picking and Growing for Unforgetting Continual Learning (NeurIPS2019)[paper][code]
- Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning (ICMR2019) [paper][code]
- Towards Training Recurrent Neural Networks for Lifelong Learning (Neural Computation 2019) [paper]
- Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay (IJCAI2019) [paper]
- IL2M: Class Incremental Learning With Dual Memory (ICCV2019) [paper]
- Incremental Learning Using Conditional Adversarial Networks (ICCV2019) [paper]
- Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability (KDD2019) [paper]
- Random Path Selection for Incremental Learning (NeurIPS2019) [paper]
- Online Continual Learning with Maximal Interfered Retrieval (NeurIPS2019) [paper]
- Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild (ICCV2019) [paper]
- Continual Learning by Asymmetric Loss Approximation with Single-Side Overestimation (ICCV2019) [paper]
- Lifelong GAN: Continual Learning for Conditional Image Generation (ICCV2019) [paper]
- Continual learning of context-dependent processing in neural networks (Nature Machine Intelligence 2019) [paper] [code]
- Large Scale Incremental Learning (CVPR2019) [paper] [code]
- Learning a Unified Classifier Incrementally via Rebalancing (CVPR2019) [paper] [code]
- Learning Without Memorizing (CVPR2019) [paper]
- Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning (CVPR2019) [paper]
- Task-Free Continual Learning (CVPR2019) [paper]
- Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting (ICML2019) [paper]
- Efficient Lifelong Learning with A-GEM (ICLR2019) [paper] [code]
- Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference (ICLR2019) [paper] [code]
- Overcoming Catastrophic Forgetting via Model Adaptation (ICLR2019) [paper]
- A comprehensive, application-oriented study of catastrophic forgetting in DNNs (ICLR2019) [paper]
- Memory Replay GANs: learning to generate images from new categories without forgetting (NIPS2018) [paper] [code]
- Reinforced Continual Learning (NIPS2018) [paper] [code]
- Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting (NIPS2018) [paper]
- Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting (R-EWC) (ICPR2018) [paper] [code]
- Exemplar-Supported Generative Reproduction for Class Incremental Learning (BMVC2018) [paper] [code]
- End-to-End Incremental Learning (ECCV2018) [paper][code]
- Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence (ECCV2018)[paper]
- Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights (ECCV2018) [paper] [code]
- Memory Aware Synapses: Learning what (not) to forget (ECCV2018) [paper] [code]
- Lifelong Learning via Progressive Distillation and Retrospection (ECCV2018) [paper]
- PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning (CVPR2018) [paper] [code]
- Overcoming Catastrophic Forgetting with Hard Attention to the Task (ICML2018) [paper] [code]
- Lifelong Learning with Dynamically Expandable Networks (ICLR2018) [paper]
- FearNet: Brain-Inspired Model for Incremental Learning (ICLR2018) [paper]
- Incremental Learning of Object Detectors Without Catastrophic Forgetting (ICCV2017) [paper]
- Overcoming catastrophic forgetting in neural networks (EWC) (PNAS2017) [paper] [code] [code]
- Continual Learning Through Synaptic Intelligence (ICML2017) [paper] [code]
- Gradient Episodic Memory for Continual Learning (NIPS2017) [paper] [code]
- iCaRL: Incremental Classifier and Representation Learning (CVPR2017) [paper] [code]
- Continual Learning with Deep Generative Replay (NIPS2017) [paper] [code]
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (NIPS2017) [paper] [code]
- Expert Gate: Lifelong Learning with a Network of Experts (CVPR2017) [paper]
- Encoder Based Lifelong Learning (ICCV2017) [paper]