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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.

105 papers of 11,817 · showing 101–105Sort Recent · Most cited
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  1. 2011
    Adaptive incremental learning in neural networksAbdelhamid Bouchachia, Nadia NedjahNeurocomputing · University of Klagenfurt · Universidade do Estado do Rio de Janeiro
  2. 2011
    Extreme and incremental learning based single-hidden-layer regularization ridgelet networkShuyuan Yang, Min Wang, Licheng JiaoNeurocomputing · Xidian University
  3. 2009
    Incremental learning of sequence patterns with a modular network modelIchiro Igari, Jun TaniNeurocomputing · RIKEN Center for Brain Science
  4. 2006
    A new ARTMAP-based neural network for incremental learningMu-Chun Su, Jonathan Lee, Kuo-Lung HsiehNeurocomputing · National Central University
  5. 1995
    A neural network architecture for incremental learningShigetoshi Shiotani, Toshio Fukuda, Takanori ShibataNeurocomputing · Nagoya University
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.