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.

8 papers of 8,653Sort Recent · Most cited
  1. 2026
    LCA: Local Classifier Alignment for Continual LearningTung Anh Tran, Danilo Vasconcellos Vargas, Khoat ThanICLR
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  2. 2023
    Continual variational dropout: a view of auxiliary local variables in continual learningNam Le Hai, T.T. Nguyen, Linh Ngo Van … Khoat ThanMachine Learning · FPT University · Hanoi University of Science and Technology · +1
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  3. 2023
    Sharpness and Gradient Aware Minimization for Memory-based Continual LearningLam Tran Tung, Viet Nguyen Van, Phi-Hung Hoang, Khoat ThanInternational Symposium on Information and Communication… · Hanoi University of Science and Technology
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  4. 2023PDF ↗
  5. 2022PDF ↗
  6. 2022
    Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture ApproximationHoang Phan, Anh Phan Tuan, Son Nguyen … Khoat ThanSpringer LNCS · VinUniversity · Hanoi University of Science and Technology
  7. 2022
    Auxiliary Local Variables for Improving Regularization/Prior Approach in Continual LearningLinh Ngo Van, Nam Le Hai, Hoang Pham, Khoat ThanSpringer LNCS · Hanoi University of Science and Technology
  8. 2019
    How to make a machine learn continuously: a tutorial of the Bayesian approachKhoat Than, Xuan Bui, Tung Nguyen-Trong … Anh Nguyen‐DucArtificial Intelligence and Machine Learning for Multi-Do… · Hanoi University of Science and Technology
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.