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.

6 papers of 11,817Sort Recent · Most cited
  1. 2022
    Cooperative data-driven modelingAleksandr Dekhovich, O. Taylan Turan, Jiaxiang Yi, Miguel A. BessaComputer Methods in Applied Mechanics and Engineering · Delft University of Technology · Brown University
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  2. 2022
    FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at EdgeYaxin Luopan, Rui Han, Qinglong Zhang … Lydia Y. ChenICDE · Beijing Institute of Technology · Beijing Research Institute of Mechanical and Electrical Technology · +1
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  3. 2022
    Continual prune-and-select: class-incremental learning with specialized subnetworksAleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. BessaApplied Intelligence · Delft University of Technology · Brown University
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  4. 2021
    Modeling Team Dynamics for the Characterization and Prediction of Delays in User StoriesElvan Kula, Arie van Deursen, Georgios GousiosIEEE/ACM International Conference on Automated Software E… · Delft University of Technology
  5. 2020
    A Hybrid Recursive Implementation of Broad Learning With Incremental FeaturesDi Liu, Simone Baldi, Wenwu Yu, C. L. Philip ChenTNNLS · Southeast University · Delft University of Technology · +1
  6. 2011
    Nonlinear multi-model ensemble prediction using dynamic Neural Network with incremental learningMichael Siek, Dimitri SolomatineIJCNN · IHE Delft Institute for Water Education · Delft University of Technology
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.