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
    Data Poisoning Attack Aiming the Vulnerability of Continual LearningGyojin Han, Jaehyun Choi, Hyeong Gwon Hong, Junmo KimICIP · Korea Advanced Institute of Science and Technology · International Graduate School of English
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  2. 2022
    Exemplar-Free Online Continual LearningJiangpeng He, Fengqing ZhuICIP · Purdue University West Lafayette
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  3. 2022
    Learning an Evolved Mixture Model for Task-Free Continual LearningFei Ye, Adrian G. BorşICIP · University of York
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  4. 2022
    Contrastive Learning for Online Semi-Supervised General Continual LearningNicolas Michel, Romain Negrel, Giovanni Chierchia, Jean‐François BercherICIP · Centre National de la Recherche Scientifique · Laboratoire d'Informatique Gaspard-Monge · +1
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  5. 2022
    Continual Learning in Vision TransformerMana Takeda, ‪Keiji Yanai‬ICIP · University of Electro-Communications
  6. 2022
    D-CBRS: Accounting for Intra-Class Diversity in Continual LearningYasin Fındık, Farhad Pourkamali‐AnarakiICIP · University of Massachusetts Lowell · University of Massachusetts Amherst
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  7. 2022
    Unsupervised Generative Variational Continual LearningLiu Guimeng, Yang Guo, Cheryl Wong Sze Yin … Savitha RamasamyICIP · Nanyang Technological University · Agency for Science, Technology and Research · +2
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.