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.

9 papers of 8,653Sort Recent · Most cited
  1. 2025
    UIDAPLE: Unsupervised Incremental Domain Adaptation through Adaptive Prompt LearningSamrat Kumar Mukherjee, Tanuj Sur, Saurish Seksaria … Biplab BanerjeeICASSP · Indian Institute of Technology Bombay · Chennai Mathematical Institute · +1
  2. 2023
    Correction to TINS 1828 Contributions by metaplasticity to solving the Catastrophic Forgetting Problem: (Trends in Neurosciences, 45:9 p:656-666, 2022).Peter Jedlička, Matúš Tomko, Anthony Robins, Wickliffe C. AbrahamTrends in Neurosciences · Goethe University Frankfurt · Justus-Liebig-Universität Gießen · +5
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  3. 2020
    A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World LearningMartin Mundt, Yongwon Hong, Iuliia Pliushch, Visvanathan RameshNeural Networks · Goethe University Frankfurt · Technische Universität Darmstadt · +1
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  4. 2022
    Contributions by metaplasticity to solving the Catastrophic Forgetting Problem.Peter Jedlička, Matúš Tomko, Anthony Robins, Wickliffe C. AbrahamTrends in Neurosciences · Goethe University Frankfurt · Justus-Liebig-Universität Gießen · +6
  5. 2019
    Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set RecognitionMartin Mundt, Iuliia Pliushch, Sagnik Majumder … Visvanathan RameshJournal of Imaging · Goethe University Frankfurt · The University of Texas at Austin · +1
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  6. 2021
    Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without ForgettingAnna Kukleva, Hilde Kuehne, Bernt SchieleICCV · Max Planck Society · Max Planck Innovation · +4
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  7. 2021
    A Procedural World Generation Framework for Systematic Evaluation of Continual LearningTimm Hess, Martin Mundt, Iuliia Pliushch, Visvanathan RameshNeurIPS · Goethe University Frankfurt
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  8. 2021
    Avalanche: an End-to-End Library for Continual LearningVincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu … Davide MaltoniCVPR · University of Pisa · University of Bologna · +12
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  9. 2021
    Neural Architecture Search of Deep Priors: Towards Continual Learning without Catastrophic InterferenceMartin Mundt, Iuliia Pliushch, Visvanathan RameshCVPR · Goethe University Frankfurt
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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.