Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 8,653Sort Recent · Most cited
  1. 2021
    Semi-Supervised Class Incremental LearningAlexis Lechat, Stéphane Herbin, Frédéric JurieICPR · Centre National de la Recherche Scientifique · École Nationale Supérieure d'Ingénieurs de Caen · +5
  2. 2021
    Energy Minimum Regularization in Continual LearningXiaobin Li, Lianlei Shan, Minglong Li, Weiqiang WangICPR · University of Chinese Academy of Sciences
  3. 2021
    Class-Incremental Learning with Topological Schemas of Memory SpacesXinyuan Chang, Xiaoyu Tao, Xiaopeng Hong … Yihong GongICPR · Xi'an Jiaotong University
  4. 2021
    Selecting Useful Knowledge from Previous Tasks for Future Learning in a Single NetworkFeifei Shi, Peng Wang, Zhongchao Shi, Yong RuiICPR · Lenovo (China)
  5. 2021
    Dual-Memory Model for Incremental Learning: The Handwriting Recognition Use CaseM. Piot, Berangere Bourdoulous, Jordan González … Lionel PrévostICPR · ESIEA University
  6. 2021
    Incrementally Zero-Shot Detection by an Extreme Value AnalyzerSixiao Zheng, Yanwei Fu, Yanxi HouICPR · Fudan University
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  7. 2021
    Few-Shot Class Incremental Learning with Generative Feature ReplayAbhilash Shankarampeta, Koichiro YamauchiICPR · Indian Institute of Technology Guwahati · Chubu University
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.