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.

11 papers of 11,817Sort Recent · Most cited
  1. 2000
    IFOSART: a noise resistant neural network capable of incremental learningAllan Loh, M. Robey, Geoff WestICPR · Curtin University
  2. 2000
    TRANSFERRING LEARNED KNOWLEDGE IN A LIFELONG LEARNING MOBILE ROBOT AGENTJoseph A. O’SullivanWorld Scientific series in robotics and intelligent systems · Carnegie Mellon University
  3. 2000
    Neural networks with a self-refreshing memory: Knowledge transfer in sequential learning tasks without catastrophic forgettingBernard Ans, Stéphane RoussetConnection Science · Institut polytechnique de Grenoble · Université Pierre Mendès France · +2
  4. 2000
    Age of acquisition effects in adult lexical processing reflect loss of plasticity in maturing systems: insights from connectionist networks.Andrew W. Ellis, Matthew A. Lambon RalphJournal of Experimental Psychology Learning Memory and Co… · University of York · MRC Cognition and Brain Sciences Unit · +1
  5. 2000
    Application of genetic programming for multicategory pattern classificationJ. K. Kishore, L.M. Patnaik, V. Mani, V.K. AgrawalIEEE Transactions · Indian Space Research Organisation · Indian Institute of Science Bangalore
  6. 2000
  7. 2000
    Updating a priori information in fuzzy pattern recognition to improve classification performanceSameer SinghJournal of Intelligent & Fuzzy Systems · University of Exeter
  8. 2000
    Sandplay Therapy: A Dialectical ProcessElena VallarinoJournal of Sandplay Therapy
  9. 2000
  10. 2000
    Negative Transfer Errors in Sequential Cognitive Skills: Strong-but-wrong Sequence Application.Authors pendingJournal of Experimental Psychology: Learning, Memory, and…
  11. 2000
    Synaptic Plasticity: Taming the BeastAuthors pendingNature Neuroscience
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.