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.

5 papers of 8,653Sort Recent · Most cited
  1. 2025
    The World Is Bigger! A Computationally-Embedded Perspective on the Big World HypothesisAlex Lewandowski, Adtiya A. Ramesh, Edan Meyer … Marlos C. MachadoNeurIPS
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  2. 2025
    Plastic Learning with Deep Fourier FeaturesAlex Lewandowski, Dale Schuurmans, Marlos C. MachadoICLR
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  3. 2024
    The Need for a Big World Simulator: A Scientific Challenge for Continual LearningSaurabh Kumar, Hong Jun Jeon, Alex Lewandowski, Benjamin Van RoyarXiv
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  4. 2025
    Learning Continually by Spectral RegularizationAlex Lewandowski, Bortkiewicz, Michał, Saurabh Kumar … Marlos C. MachadoICLR
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  5. 2023
    Directions of Curvature as an Explanation for Loss of PlasticityAlex Lewandowski, Haruto Tanaka, Dale Schuurmans, Marlos C. MachadoarXiv
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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.