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.

532 papers of 6,984 · showing 501–532Sort Recent · Most cited
  1. 2021
  2. 2021
    Weakly Supervised Continual LearningMatteo Boschini, Pietro Buzzega, Lorenzo Bonicelli … S. CalderaraarXiv
  3. 2021
    Efficient Continual Learning with Modular Networks and Task-Driven PriorsTom Véniat, Ludovic Denoyer, Marc’Aurelio RanzatoICLR · Meta (United States)
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  4. 2021
    River: machine learning for streaming data in PythonJacob Montiel, Max Halford, Saulo Martiello Mastelini … Albert BifetJMLR · University of Waikato · Universidade de São Paulo · +14
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  5. 2021
    A Comprehensive Study of Class Incremental Learning Algorithms for Visual TasksEden Belouadah, Adrian Popescu, Ioannis KanellosNeural Networks · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Université Paris-Saclay · +2
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  6. 2021
    Reset-Free Lifelong Learning with Skill-Space PlanningKevin Lü, Aditya Grover, Pieter Abbeel, Igor MordatchICLR · University of California, Berkeley · Stanford University · +1
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  7. 2021
    Generalized Variational Continual LearningNoel Loo, Siddharth Swaroop, Richard E. TurnerICLR · University of Cambridge
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  8. 2021
    One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic ForgettingMiao Zhang, Huiqi Li, Shirui Pan … Steven W. SuTPAMI · Beijing Institute of Technology · Monash University · +2
  9. 2021
    Linear Mode Connectivity in Multitask and Continual LearningSeyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Görür … Hassan GhasemzadehICLR · Washington State University · Google (United States)
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  10. 2021
    A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap MatrixThang Doan, Mehdi Bennani, Bogdan Mazoure … Pierre AlquierAISTATS
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  11. 2021
    Remembering for the Right Reasons: Explanations Reduce Catastrophic ForgettingSayna Ebrahimi, S. Petryk, Akash Gokul … Trevor DarrellICLR
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  12. 2021
    Continual Learning Using Bayesian Neural NetworksHonglin Li, Payam Barnaghi, Shirin Enshaeifar, Frieder GanzTNNLS · University of Surrey · UK Dementia Research Institute · +1
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  13. 2021
    Incremental Concept Learning via Online Generative Memory RecallHuaiyu Li, Weiming Dong, Bao-Gang HuTNNLS · Chinese Academy of Sciences · Beijing Academy of Artificial Intelligence · +2
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  14. 2021
    Convolutional Neural Network With Developmental Memory for Continual LearningGyeong-Moon Park, Sahng-Min Yoo, Jong-Hwan KimTNNLS · Electronics and Telecommunications Research Institute · Korea Advanced Institute of Science and Technology
  15. 2021
    Lifelong Learning of Compositional StructuresJorge A. Mendez, Eric EatonICLR · California University of Pennsylvania · University of Pennsylvania
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  16. 2021
    Anatomy of Catastrophic Forgetting: Hidden Representations and Task SemanticsVinay Ramasesh, Ethan Dyer, Maithra RaghuICLR · Google (United States) · Cornell University
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  17. 2021
    Graph-Based Continual LearningBinh Tang, David S. MattesonICLR · Cornell University
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  18. 2021
    Wandering within a World: Online Contextualized Few-Shot LearningMengye Ren, Michael L. Iuzzolino, Michael C. Mozer, Richard S. ZemelICLR · University of Toronto · University of Colorado Boulder · +1
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  19. 2021
    IncDet: In Defense of Elastic Weight Consolidation for Incremental Object DetectionLiyang Liu, Zhanghui Kuang, Yimin Chen … Wayne ZhangTNNLS · University Town of Shenzhen · Tsinghua University · +2
  20. 2021PDF ↗
  21. 2021
    Continual learning in recurrent neural networksBenjamin Ehret, Christian Henning, Maria R. Cervera … B. GreweICLR
  22. 2021
    CPR: Classifier-Projection Regularization for Continual LearningSungmin Cha, Hsiang Hsu, Taebaek Hwang … Taesup MoonICLR
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  23. 2021
    Variational Auto-Regressive Gaussian Processes for Continual LearningSanyam Kapoor, Theofanis Karaletsos, Thang D. BuiICML · Supélec · University of Applied Sciences and Arts of Southern Switzerland · +3
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  24. 2021
    Addressing Catastrophic Forgetting in Few-Shot ProblemsPauching Yap, Hippolyt Ritter, David BarberICML · University College London
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  25. 2021
    Lifelong Visual-Tactile Cross-Modal Learning for Robotic Material PerceptionWendong Zheng, Huaping Liu, Fuchun SunTNNLS · Hebei University of Technology · Tsinghua University
  26. 2021
    Continual Multiview Task Learning via Deep Matrix FactorizationGan Sun, Yang Cong, Yulun Zhang … Yun FuTNNLS · Northeastern University · Shenyang Institute of Automation · +2
  27. 2021
    Federated Continual Learning with Weighted Inter-client TransferJaehong Yoon, Wonyong Jeong, Giwoong Lee … Sung Ju HwangICML · Korea Advanced Institute of Science and Technology · Korea Institute of Science and Technology
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  28. 2021
    Novelty Detection and Online Learning for Chunk Data StreamsYi Wang, Yi Ding, Xiangjian He … Jiebo LuoTPAMI · Dalian University of Technology · University of Technology Sydney · +2
  29. 2021
    Direction Concentration Learning: Enhancing Congruency in Machine LearningYan Luo, Yongkang Wong, Mohan Kankanhalli, Qi ZhaoTPAMI · University of Minnesota · National University of Singapore
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  30. 2021
    Hierarchical Indian buffet neural networks for Bayesian continual learningSamuel Kessler, Vu Nguyen, Stefan Zohren, Stephen RobertsUAI · University of Oxford · Science Oxford
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  31. 2021
    Overcoming Catastrophic Forgetting by Bayesian Generative RegularizationPatrick H. Chen, Wei Wei, Cho‐Jui Hsieh, Bo DaiICML · University of California, Los Angeles
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  32. 2021
    BooVAE: Boosting Approach for Continual Learning of VAEAnna Kuzina, Evgenii Egorov, Evgeny BurnaevNeurIPS · Yandex (Russia) · Skolkovo Institute of Science and 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.