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. 2022
    A study of the Dream Net model robustness across continual learning scenariosMarion Mainsant, Martial Mermillod, Christelle Godin, Marina ReybozICDM · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · CEA Grenoble · +3
  2. 2022
    On the Beneficial Effects of Reinjections for Continual LearningM. Solinas, Marina Reyboz, Stéphane Rousset … Martial MermillodSN Computer Science · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · CEA Grenoble · +3
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  3. 2022
    Federated Continual Learning through distillation in pervasive computingAnastasiia Usmanova, François Portet, Philippe Lalanda, Germán VegaInternational Conference on Smart Computing · Université Grenoble Alpes
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  4. 2022
    Unseen Classes at a Later Time? No ProblemHari Chandana Kuchibhotla, Sumitra S Malagi, Shivam Chandhok, Vineeth N BalasubramanianCVPR · Indian Institute of Technology Hyderabad · Institut national de recherche en sciences et technologies du numérique · +1
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  5. 2022
    Federated Learning and catastrophic forgetting in pervasive computing: demonstration in HAR domainAnastasiia Usmanova, François Portet, Philippe Lalanda, Germán VegaIEEE International Conference on Pervasive Computing and… · Université Grenoble Alpes · Laboratoire d'Informatique de Grenoble · +2
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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.