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. 2022
    Bayesian continual learning via spiking neural networksNicolas Skatchkovsky, Hyeryung Jang, Osvaldo SimeoneFrontiers · King's College London · Dongguk University
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  2. 2022
    Brain-inspired Predictive Coding Improves the Performance of Machine Challenging TasksJangho Lee, Jeonghee Jo, Byoung-Hwa Lee … Sungroh YoonFrontiers · Seoul National University · Electronics and Telecommunications Research Institute · +1
  3. 2022
    Self-organized Learning from Synthetic and Real-World Data for a Humanoid Exercise RobotNicolas Duczek, Matthias Kerzel, Philipp Allgeuer, Stefan WermterFrontiers · Universität Hamburg
  4. 2022
    Continual Sequence Modeling With Predictive CodingLouis Annabi, Alexandre Pitti, Mathias QuoyFrontiers · Centre National de la Recherche Scientifique · Equipes Traitement de l'Information et Systèmes · +2
  5. 2022
    Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic EnvironmentsAbhiram Iyer, Karan Grewal, Akash Velu … Subutai AhmadFrontiers · Carnegie Mellon University · Stanford University · +1
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  6. 2022
    What Is Adult Hippocampal Neurogenesis Good for?Gerd KempermannFrontiers · German Center for Neurodegenerative Diseases · Center for Regenerative Therapies Dresden · +1
  7. 2022
    Is Class-Incremental Enough for Continual Learning?Andrea Cossu, Gabriele Graffieti, Lorenzo Pellegrini … Vincenzo LomonacoFrontiers · University of Pisa · Scuola Normale Superiore · +1
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  8. 2022
    Mind Your Manners! A Dataset and a Continual Learning Approach for Assessing Social Appropriateness of Robot ActionsJonas Tjomsland, Sinan Kalkan, Hatice GüneşFrontiers · University of Cambridge · Middle East Technical University
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  9. 2022
    Catastrophic Forgetting in Deep Graph Networks: A Graph Classification BenchmarkAntonio Carta, Andrea Cossu, Federico Errica, Davide BacciuFrontiers · University of Pisa · Scuola Normale Superiore
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. By default it shows the 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. The rest are one click away under “All papers”. 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.