Related work

The foundational work on continual learning, 1989 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

6 papers of 5,456Sort Recent · Most cited
  1. 2025
    Topological Mapping and Continual LearningNaoyuki Kubota, Takenori Obo, Yuichiro Toda, Naoki MasuyamaJournal of Japan Society for Fuzzy Theory and Intelligent… · Tokyo Metropolitan University · Okayama University · +1
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  2. 2024
    Clustering-Based Automatic Codeword Lengths Determination in Self-Supervised LearningTakanori Takebayashi, Naoki Masuyama, Yusuke NojimaICML · Osaka Metropolitan University · Tokyo Metropolitan University
  3. 2024
    Privacy-Preserving Continual Federated Clustering via Adaptive Resonance TheoryNaoki Masuyama, Yusuke Nojima, Yuichiro Toda … Naoyuki KubotaIEEE Access · Osaka Metropolitan University · Okayama University · +3
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  4. 2023
    Class-wise Classifier Design Capable of Continual Learning using Adaptive Resonance Theory-based Topological ClusteringNaoki Masuyama, Yusuke Nojima, Farhan Dawood, Zongying LiuApplied Sciences · Osaka Metropolitan University · Tokyo Metropolitan University · +3
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  5. 2022
    A Robust Growing Memory Network for Lifelong Learning of Intelligent AgentsWei Hong Chin, Wenbang Dou, Naoyuki Kubota, Chu Kiong LooIJCNN · Tokyo Metropolitan University · University of Malaya
  6. 2019
    Spatial Map Learning with Self-Organizing Adaptive Recurrent Incremental NetworkWei Hong Chin, Naoyuki Kubota, Chu Kiong Loo … Honghai LiuIJCNN · Tokyo Metropolitan University · University of Malaya · +1
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 lists only 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. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.