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.

7 papers of 11,817Sort Recent · Most cited
  1. 2022
    Memory Population in Continual Learning via Outlier EliminationJulio Hurtado, Alain Raymond-Sáez, Vladimir Araujo … Davide BacciuICCV · University of Pisa · Pontificia Universidad Católica de Chile · +1
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  4. 2022
    A Continual Deepfake Detection Benchmark: Dataset, Methods, and EssentialsChuqiao Li, Zhiwu Huang, Danda Pani Paudel … Luc Van GoolWACV · Singapore Management University · Xi'an Jiaotong University · +2
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  5. 2022
    Three types of incremental learningGido M. van de Ven, Tinne Tuytelaars, Andreas S. ToliasNature Machine Intelligence · Baylor College of Medicine · University of Cambridge · +2
  6. 2022
    Entropy-based Stability-Plasticity for Lifelong LearningVladimir Araujo, Julio Hurtado, Álvaro Soto, Marie‐Francine MoensCVPR · KU Leuven · University of Pisa · +1
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  7. 2022
    Sound and Visual Representation Learning with Multiple Pretraining TasksArun Balajee Vasudevan, Dengxin Dai, Luc Van GoolCVPR · ETH Zurich · KU Leuven
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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.