Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

10 papers of 8,653Sort Recent · Most cited
  1. 2022
    Same State, Different Task: Continual Reinforcement Learning without InterferenceSamuel Kessler, Jack Parker-Holder, Philip Ball … Stephen RobertsAAAI · University of Oxford
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  2. 2022
    Adaptive Orthogonal Projection for Batch and Online Continual LearningYiduo Guo, Wenpeng Hu, Dongyan Zhao, Bing LiuAAAI · Peking University · King University · +1
  3. 2022
    Lifelong Person Re-identification by Pseudo Task Knowledge PreservationWenhang Ge, Junlong Du, Ancong Wu … Wei‐Shi ZhengAAAI · Sun Yat-sen University · Tencent (China)
  4. 2022
    Continual Learning through Retrieval and ImaginationZhen Wang, Liu Liu, Yiqun Duan, Dacheng TaoAAAI · The University of Sydney · University of Technology Sydney
  5. 2022
    Static-Dynamic Co-Teaching for Class-Incremental 3D Object DetectionNa Zhao, Gim Hee LeeAAAI · National University of Singapore
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  6. 2022
    Lifelong Generative Modelling Using Dynamic Expansion Graph ModelFei Ye, Adrian G. BorşAAAI · University of York
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  7. 2022
    Lifelong Hyper-Policy Optimization with Multiple Importance Sampling RegularizationPierre Liotet, Francesco Vidaich, Alberto Maria Metelli, Marcello RestelliAAAI · Politecnico di Milano · University of Padua
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  8. 2022
    Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative ReplayHitesh Vaidya, Travis Desell, Alexander G. OrorbiaAAAI · Rochester Institute of Technology
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  9. 2022
    Learning to Transfer with von Neumann Conditional DivergenceAmmar Shaker, Shujian Yu, Daniel Oñoro-RubioAAAI · Sharp Laboratories of Europe (United Kingdom) · Centre for Arctic Gas Hydrate, Environment and Climate · +2
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  10. 2022
    Learngene: From Open-World to Your Learning TaskQiufeng Wang, Xin Geng, Shuxia Lin … Ning XuAAAI
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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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.