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.

4 papers of 8,653Sort Recent · Most cited
  1. 2026
    Continual Learning by Regularization in Row Space of Weight Matrix of Previous Task for Deep Neural NetworkHonoka Yamashita, Takio Kurita, Masaki OnishiInternational Conference on Agents and Artificial Intelli… · University of Tsukuba · National Institute of Advanced Industrial Science and Technology
  2. 2021
    Statistical Mechanical Analysis of Catastrophic Forgetting in Continual Learning with Teacher and Student NetworksHaruka Asanuma, Shiro Takagi, Yoshihiro Nagano … Masato OkadaJournal of the Physical Society of Japan · The University of Tokyo · University of Tsukuba · +1
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  3. 2019
    Application of a Selective Desensitization Neural Network to Concept Drift ProblemsIchiba Tomoki, Kazumasa Horie, Someno Shoichi … Masahiko MoritaJournal of Signal Processing · University of Tsukuba
  4. 2018
    Stepwise PathNet: Transfer Learning Algorithm to Improve Network Structure VersatilityShunsuke Imai, Hajime NobuharaIEEE International Conference on Systems, Man, and Cybern… · University of Tsukuba
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 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.