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.

4 papers of 11,817Sort Recent · Most cited
  1. 2022
    Towards Building a Distributed Virtual Flow Meter via Compressed Continual LearningHasan Asyari Arief, Peter J. Thomas, Kevin Constable, Aggelos K. KatsaggelosSensors · Northwestern University · NORCE Research AS · +1
  2. 2022
    General Image Fusion for an Arbitrary Number of Inputs Using Convolutional Neural NetworksYifan Xiao, Zhixin Guo, Peter Veelaert, Wilfried PhilipsSensors · Ghent University
  3. 2022
    Continual Learning Objective for Analyzing Complex Knowledge RepresentationsAsad Mansoor Khan, Taimur Hassan, Muhammad Usman Akram … Naoufel WerghiSensors · National University of Sciences and Technology · Khalifa University of Science and Technology · +1
  4. 2022
    Unknown Object Detection Using a One-Class Support Vector Machine for a Cloud–Robot SystemRaihan Kabir, Yutaka Watanobe, Md. Rashedul Islam … Md. Mostafizer RahmanSensors · University of Aizu · University of Asia Pacific
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.