unify

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
2019 Springer LNCS Clear all
  1. 2019
    Measuring Catastrophic Forgetting in Visual Question AnsweringClaudio Greco, Barbara Plank, Raquel Fernández, Raffaella BernardiSpringer LNCS · University of Trento · IT University of Copenhagen · +1
  2. 2019
    REMIND Your Neural Network to Prevent Catastrophic ForgettingTyler L. Hayes, Kushal Kafle, Robik Shrestha … Christopher KananSpringer LNCS · Rochester Institute of Technology · Adobe Systems (United States) · +2
    PDF ↗
  3. 2019
    Continual Learning of Image Translation Networks Using Task-Dependent Weight Selection MasksMatsumoto Asato, ‪Keiji Yanai‬Springer LNCS · University of Electro-Communications
  4. 2019
    A Study on Catastrophic Forgetting in Deep LSTM NetworksMonika Schak, Alexander GepperthSpringer LNCS · Fulda University of Applied Sciences
  5. 2019
    Continual Learning Exploiting Structure of Fractal Reservoir ComputingTaisuke Kobayashi, Toshiki SuginoSpringer LNCS · Nara Institute of Science and Technology
  6. 2019
    Strategies for Improving Single-Head Continual Learning PerformanceAlaa El Khatib, Fakhri KarraySpringer LNCS · University of Waterloo
  7. 2019
    Simplified Computation and Interpretation of Fisher Matrices in Incremental Learning with Deep Neural NetworksAlexander Gepperth, Florian WiechSpringer LNCS · Fulda University of Applied Sciences
  8. 2019
    Overcoming Catastrophic Interference with Bayesian Learning and Stochastic Langevin DynamicsMikhail Leontev, Alexander Mikheev, Kirill Sviatov, Sergey SukhovSpringer LNCS · Ulyanovsk State University · Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences · +1
  9. 2019
    Lifelong Learning Starting From ZeroClaes Strannegård, Herman Carlström, Niklas Engsner … Morteza Haghir ChehreghaniSpringer LNCS · Chalmers University of Technology
    PDF ↗
  10. 2019
    MaxEntropy Pursuit Variational InferenceEvgenii Egorov, Kirill Neklydov, Ruslan Kostoev, Evgeny BurnaevSpringer LNCS · Skolkovo Institute of Science and Technology · National Research University Higher School of Economics · +1
    PDF ↗
  11. 2019
    Central-Diffused Instance Generation Method in Class Incremental LearningMing-Yu Liu, Yijie WangSpringer LNCS · National University of Defense 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.