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
    Optimal Developmental Learning for Multisensory and Multi-Teaching ModalitiesJulia Knoll, Jacob Honer, Samuel Church, Juyang WengIEEE International Conference on Development and Learning… · Michigan State University
  2. 2021
    Federated Continuous Learning With Broad Network ArchitectureJunqing Le, Xinyu Lei, Nankun Mu … Xiaofeng LiaoIEEE Trans. Cybernetics · Southwest University · Michigan State University · +2
  3. 2021
    Spatio-Temporal Multi-Task Learning via Tensor DecompositionJianpeng Xu, Jiayu Zhou, Pang‐Ning Tan … Lifeng LuoTKDE · Michigan State University
  4. 2019
    Emergent Multilingual Language Acquisition Using Developmental NetworksJuan Castro-Garcia, Juyang WengIJCNN · Michigan State University
  5. 2019
    Ultra-local adaptation due to genetic accommodationSyuan‐Jyun Sun, Andrew M. Catherall, Sónia Pascoal … Rebecca M. KilnerbioRxiv · University of Cambridge · Michigan State University · +1
  6. 2016
  7. 2001
    Learn++: an incremental learning algorithm for supervised neural networksRobi Polikar, L. Upda, S.S. Upda, Vasant HonavarIEEE Transactions · Rowan University · Iowa State University · +1
  8. 1999
    Incremental learning for Bayesian classification of imagesAditya Vailaya, Anil K. JainICIP · Michigan State University
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.