Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

720 papers of 6,984 · showing 701–720Sort Recent · Most cited
  1. 2022
    Learning to Classify With Incremental New ClassDa-Wei Zhou, Yang Yang, De-Chuan ZhanTNNLS · Nanjing University · Nanjing University of Science and Technology
  2. 2022
    Memory Recall: A Simple Neural Network Training Framework Against Catastrophic ForgettingBaosheng Zhang, Yuchen Guo, Yipeng Li … Qionghai DaiTNNLS · Tsinghua University · Tsinghua–Berkeley Shenzhen Institute
  3. 2022
    Adaptive Progressive Continual LearningJu Xu, Jin Ma, Xuesong Gao, Zhanxing ZhuTPAMI · Peking University · Shandong University · +4
  4. 2022
    Lifelong Teacher-Student Network LearningFei Ye, Adrian G. BorşTPAMI · University of York
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  5. 2022
    Continual Novelty DetectionRahaf Aljundi, Daniel Olmeda Reino, Nikolay Chumerin, Richard E. TurnerCoLLAs
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  6. 2022
    Incremental Deep Neural Network Learning Using Classification Confidence ThresholdingJustin Leo, Jugal KalitaTNNLS · University of Colorado Colorado Springs
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  7. 2022
    Learngene: From Open-World to Your Learning TaskQiufeng Wang, Xin Geng, Shuxia Lin … Ning XuAAAI
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  8. 2022PDF ↗
  9. 2022
    Online Coreset Selection for Rehearsal-based Continual LearningJaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju HwangICLR · Korea Advanced Institute of Science and Technology · Korea Institute of Science and Technology
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  10. 2022
    Using top-down modulation to optimally balance shared versus separated task representationsPieter Verbeke, Tom VergutsNeural Networks · Ghent University Hospital
  11. 2022
    TAG: Task-based Accumulated Gradients for Lifelong learningPranshu Malviya, Balaraman Ravindran, Sarath ChandarCoLLAs
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  12. 2022
    Memory-Efficient Class-Incremental Learning for Image ClassificationHanbin Zhao, Hui Wang, Yongjian Fu … Xi LiTNNLS · Zhejiang University of Science and Technology · Shanghai Advanced Research Institute
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  13. 2022
    How Well Does Self-Supervised Pre-Training Perform with Streaming Data?Dapeng Hu, Shipeng Yan, Qizhengqiu Lu … Jiashi FengICLR
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  14. 2022
    New Insights on Reducing Abrupt Representation Change in Online Continual LearningLucas Caccia, Rahaf Aljundi, Nader Asadi … Eugene BelilovskyICLR
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  15. 2022
    A Two-Stream Continual Learning System With Variational Domain-Agnostic Feature ReplayQicheng Lao, Xiang Jiang, Mohammad Havaei, Yoshua BengioTNNLS · West China Medical Center of Sichuan University
  16. 2022
    Beneficial Perturbation Network for Designing General Adaptive Artificial Intelligence SystemsShixian Wen, Amanda Rios, Yunhao Ge, Laurent IttiTNNLS · University of Southern California
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  17. 2022
    What and How: Generalized Lifelong Spectral Clustering via Dual MemoryGan Sun, Yang Cong, Jiahua Dong … Haibin YuTPAMI · Shenyang Institute of Automation · Chinese Academy of Sciences · +2
  18. 2022
    Lifelong Incremental Reinforcement Learning With Online Bayesian InferenceZhi Wang, Chunlin Chen, Daoyi DongTNNLS · Nanjing University · University of Canberra · +1
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  19. 2022
    How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of InterpolationEkdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert P. DickCoLLAs · University of Michigan
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  20. 2022
    Energy-Based Models for Continual LearningShuang Li, Yilun Du, Gido M. van de Ven, Igor MordatchCoLLAs · Massachusetts Institute of Technology
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About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.