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.

7 papers of 8,653Sort Recent · Most cited
  1. 2019
    A Continual Learning Survey: Defying Forgetting in Classification TasksMatthias Delange, Rahaf Aljundi, Marc Masana … Tinne TuytelaarsTPAMI · Computer Vision Center · Huawei Technologies (Canada)
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  2. 2019PDF ↗
  3. 2019
    Continual learning: A comparative study on how to defy forgetting in classification tasksMatthias De Lange, Rahaf Aljundi, Marc Masana … T. TuytelaarsTPAMI
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  4. 2019
    Online Continual Learning with Maximally Interfered RetrievalRahaf Aljundi, Lucas Caccia, Eugene Belilovsky … Tinne TuytelaarsarXiv · McGill University · Université de Montréal · +1
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  5. 2019
    Task-Free Continual LearningRahaf Aljundi, Klaas Kelchtermans, Tinne TuytelaarsCVPR · KU Leuven
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  6. 2019
    Gradient based sample selection for online continual learningRahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua BengioNeurIPS · KU Leuven · National University of Singapore · +1
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  7. 2019
    Selfless Sequential LearningRahaf Aljundi, Marcus Rohrbach, Tinne TuytelaarsICLR
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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.