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. 2021
    Ex-Model: Continual Learning from a Stream of Trained ModelsAntonio Carta, Andrea Cossu, Vincenzo Lomonaco, Davide BacciuCVPR · University of Pisa · Scuola Normale Superiore
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  2. 2021
    Is Class-Incremental Enough for Continual Learning?Andrea Cossu, Gabriele Graffieti, Lorenzo Pellegrini … Vincenzo LomonacoFrontiers · University of Pisa · Scuola Normale Superiore · +1
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  3. 2021
    Distilled Replay: Overcoming Forgetting through Synthetic SamplesAndrea Rosasco, Antonio Carta, Andrea Cossu … Davide BacciuSpringer LNCS · University of Pisa · Scuola Normale Superiore
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  4. 2021
    Continual Learning for Recurrent Neural Networks: an Empirical EvaluationAndrea Cossu, Antonio Carta, Vincenzo Lomonaco, Davide BacciuNeural Networks · University of Pisa · Scuola Normale Superiore · +1
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  5. 2021
    Continual Learning with Echo State NetworksAndrea Cossu, Davide Bacciu, Antonio Carta … Vincenzo LomonacoESANN 2021 proceedings · University of Pisa · Scuola Normale Superiore · +1
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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.