Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 11,817Sort Recent · Most cited
  1. 2018
    StackNet: Stacking feature maps for Continual learningKim Jangho, Jeesoo Kim, Nojun KwakCVPR · Seoul National University
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  2. 2018
    Learning Without MemorizingPrithviraj Dhar, Rajat Singh, Kuan–Chuan Peng … Rama ChellappaCVPR · University of Maryland, College Park · Siemens (Germany)
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  3. 2018
    Task-Free Continual LearningRahaf Aljundi, Klaas Kelchtermans, Tinne TuytelaarsCVPR · KU Leuven
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  4. 2018
    A Perceptual Prediction Framework for Self Supervised Event SegmentationSathyanarayanan N. Aakur, Sudeep SarkarCVPR · University of South Florida
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  5. 2018
    NeuralNetwork-Viterbi: A Framework for Weakly Supervised Video LearningAlexander Richard, Hilde Kuehne, Ahsan Iqbal, Jüergen GallCVPR · University of Bonn
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  6. 2018
    New Metrics and Experimental Paradigms for Continual LearningTyler L. Hayes, Ronald Kemker, Nathan D. Cahill, Christopher KananCVPR · Rochester Institute of Technology
  7. 2018
    Subset Replay Based Continual Learning for Scalable Improvement of Autonomous SystemsPratik Prabhanjan Brahma, Adrienne OthonCVPR · Volkswagen Group (United States)
  8. 2018
    Dynamic Few-Shot Visual Learning Without ForgettingSpyros Gidaris, Nikos KomodakisCVPR
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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 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.