Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 11,817Sort Recent · Most cited
  1. 2021
    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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  2. 2021
    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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  3. 2021
    Modeling Morphology With Linear Discriminative Learning: Considerations and Design ChoicesMaria Heitmeier, Yu‐Ying Chuang, R. Harald BaayenFrontiers · University of Tübingen
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  4. 2021
    Coffee With a Hint of Data: Towards Using Data-Driven Approaches in Personalised Long-Term InteractionsBahar Irfan, Mehdi Hellou, Tony BelpaemeFrontiers · University of Plymouth · Ghent University
  5. 2021
    A Brain-Inspired Homeostatic Neuron Based on Phase-Change Memories for Efficient Neuromorphic ComputingIrene Muñoz-Martín, S. Bianchi, Shahin Hashemkhani … Daniele IelminiFrontiers · Politecnico di Milano
  6. 2021
    Learning Then, Learning Now, and Every Second in Between: Lifelong Learning With a Simulated Humanoid RobotAleksej Logacjov, Matthias Kerzel, Stefan WermterFrontiers · Universität Hamburg
  7. 2021
    Lifelong Personalization via Gaussian Process Modeling for Long-Term HRISamuel Spaulding, Jocelyn Shen, Hae Won Park, Cynthia BreazealFrontiers · Massachusetts Institute of Technology
  8. 2021
    Intensified Job Demands and Cognitive Stress Symptoms: The Moderator Role of Individual CharacteristicsJohanna Rantanen, Pessi Lyyra, Taru Feldt … Tiina ParviainenFrontiers · University of Jyväskylä
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.