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.

5 papers of 11,817Sort Recent · Most cited
  1. 2021
    Class-incremental Learning using a Sequence of Partial Implicitly Regularized ClassifiersSobirdzhon Bobiev, Albina Khusainova, Adil Khan, S. M. Ahsan Kazmi... International Florida Artificial Intelligence Researc… · Innopolis University · University of the West of England
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  2. 2021
    Continuous learning with random memory for object detection in robotic applicationsIvan Nenakhov, Ruslan Mazhitov, Kirill Artemov … Sergey A. KolyubinInternational Conference "Nonlinearity, Information and R… · ITMO University · Siberian Academy of Finance and Banking · +1
  3. 2021
    Spatial Memory in a Spiking Neural Network with Robot EmbodimentSergey A. Lobov, A.I. Zharinov, Valeri A. Makarov, Victor KazantsevSensors · Immanuel Kant Baltic Federal University · Innopolis University · +3
  4. 2017
    Pseudorehearsal in Actor-Critic Agents with Neural Network Function ApproximationVladimir Marochko, Leonard Johard, Manuel Mazzara, Luca LongoInternational Conference on Advanced Information Networki… · Innopolis University
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  5. 2017
    Pseudorehearsal in value function approximationVladimir Marochko, Leonard Johard, Manuel MazzaraSmart innovation, systems and technologies · Innopolis University
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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.