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.

7 papers of 8,653Sort Recent · Most cited
  1. 2025
    Continual Contrastive Learning on Tabular Data with Out of DistributionAchmad Ginanjar, Xue Li, Priyanka Singh, Wen HuaThe European Symposium on Artificial Neural Networks · Queensland University of Technology · The University of Queensland · +1
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  2. 2020
    A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean ProblemsIsidro M. Alvarez, Trung B. Nguyen, Will N. Browne, Mengjie ZhangEvolutionary Computation · Victoria University of Wellington · Statistics New Zealand · +1
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  3. 2023
    CL3: Generalization of Contrastive Loss for Lifelong LearningKaushik Roy, Christian Simon, Peyman Moghadam, Mehrtash HarandiJournal of Imaging · Commonwealth Scientific and Industrial Research Organisation · Data61 · +3
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  4. 2023
    Flashback for Continual LearningLeila Mahmoodi, Mehrtash Harandi, Peyman MoghadamICCV · Commonwealth Scientific and Industrial Research Organisation · Australian Regenerative Medicine Institute · +3
  5. 2022
    Uncertainty Estimation With Neural Processes for Meta-Continual LearningXuesong Wang, Lina Yao, Xianzhi Wang … Sen WangTNNLS · University of Technology Sydney · UNSW Sydney · +4
  6. 2022
    InCloud: Incremental Learning for Point Cloud Place RecognitionJoshua Knights, Peyman Moghadam, Milad Ramezani … Clinton FookesIROS · Commonwealth Scientific and Industrial Research Organisation · Queensland University of Technology · +2
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  7. 2023
    ConCS: A Continual Classifier System for Continual Learning of Multiple Boolean ProblemsTrung B. Nguyen, Will N. Browne, Mengjie ZhangIEEE Transactions · Victoria University of Wellington · Queensland University of Technology
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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.