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.

4 papers of 8,653Sort Recent · Most cited
  1. 2020
    A Comprehensive Study of Class Incremental Learning Algorithms for Visual TasksEden Belouadah, Adrian Popescu, Ioannis KanellosNeural Networks · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Université Paris-Saclay · +2
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  2. 2020
    ScaIL: Classifier Weights Scaling for Class Incremental LearningEden Belouadah, Adrian PopescuWACV · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Université Paris-Saclay · +1
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  3. 2020
    Initial Classifier Weights Replay for Memoryless Class Incremental LearningEden Belouadah, Adrian Popescu, Ioannis KanellosBMVC · Commissariat à l'Énergie Atomique et aux Énergies Alternatives
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  4. 2020
    Active Class Incremental Learning for Imbalanced DatasetsEden Belouadah, Adrian Popescu, Umang Aggarwal, Léo SaciSpringer LNCS · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Laboratoire d'Intégration des Systèmes et des Technologies · +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.