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.

5 papers of 11,817Sort Recent · Most cited
  1. 2022
    Quantum continual learning of quantum data realizing knowledge backward transferHaozhen Situ, Tianxiang Lu, Minghua Pan, Lvzhou LiPhysica A Statistical Mechanics and its Applications · South China Agricultural University · Guilin University of Electronic Technology · +1
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  2. 2022
    SCMP-IL: an incremental learning method with super constraints on model parametersJidong Han, Zhaoying Liu, Yujian Li, Ting ZhangInternational Journal of Machine Learning and Cybernetics · Beijing University of Technology · Guilin University of Electronic Technology
  3. 2022
    Deep sparse representation via deep dictionary learning for reinforcement learningJianhao Tang, Zhenni Li, Shengli Xie … Xueni ChenChinese Control Conference (CCC) · Guangdong University of Technology · Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality · +1
  4. 2020
    Prototype-Based Discriminative Feature Representation for Class-incremental Cross-modal RetrievalShaoquan Zhu, Yong Feng, Mingliang Zhou … Ran WeiInternational Journal of Pattern Recognition and Artifici… · Ministry of Education of the People's Republic of China · Chongqing University · +3
  5. 2014
    Efficient class incremental learning for multi-label classification of evolving data streamsZhongwei Shi, Yun Xue, Yimin Wen, Guoyong CaiIJCNN · Guilin University of Electronic Technology · Hunan City 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.