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. 2022
    Automated Continual Learning of Defect Identification in Coherent Diffraction ImagingOrçun Yildiz, Henry Chan, Krishnan Raghavan … Tom PeterkaIEEE/ACM International Workshop on Artificial Intelligenc… · Argonne National Laboratory · University of Illinois Chicago
  2. 2022
    Continual Learning via Dynamic ProgrammingRanganath Krishnan, Prasanna BalaprakashICPR · Argonne National Laboratory
  3. 2022
    Large Scale Caching and Streaming of Training Data for Online Deep LearningJie Liu, Bogdan Nicolae, Dong Li … Ian FosterWorkshop on AI and Scientific Computing at Scale using Fl… · University of California, Merced · Argonne National Laboratory
  4. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
  5. 2022
    Reconfigurable perovskite nickelate electronics for artificial intelligenceHaitian Zhang, Tae Joon Park, A N M Nafiul Islam … Shriram RamanathanScience · Purdue University West Lafayette · Pennsylvania State University · +6
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.