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
  1. 2026PDF ↗
  2. 2026
    LDTC: Lifelong deep temporal clustering for multivariate time seriesZhi Wang, Yanni Li, Pingping Zheng, Yiyuan JiaoarXiv
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  3. 2026
    MoETTA: Test-Time Adaptation Under Mixed Distribution Shifts with MoE-LayerNormXiao Fan, Jingyan Jiang, Zhaoru Chen … Zhi WangAAAI
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  4. 2025PDF ↗
  5. 2024PDF ↗
  6. 2022
    Efficient Bayesian Policy Reuse With a Scalable Observation Model in Deep Reinforcement LearningJinmei Liu, Zhi Wang, Chunlin Chen, Daoyi DongTNNLS · Nanjing University · University of Canberra · +1
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  7. 2022
    A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement LearningZhi Wang, Chunlin Chen, Daoyi DongIEEE Trans. Cybernetics · Nanjing University · University of Canberra · +1
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  8. 2020
    Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic EnvironmentsZhi Wang, Chunlin Chen, Daoyi DongTNNLS · University of Canberra · UNSW Sydney · +1
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  9. 2020
    Lifelong Incremental Reinforcement Learning With Online Bayesian InferenceZhi Wang, Chunlin Chen, Daoyi DongTNNLS · Nanjing University · University of Canberra · +1
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  10. 2019
    Incremental Reinforcement Learning With Prioritized Sweeping for Dynamic EnvironmentsZhi Wang, Chunlin Chen, Han‐Xiong Li … Tzyh‐Jong TarnIEEE/ASME Transactions on Mechatronics · Nanjing University · Central South University · +3
  11. 2019
    Incremental Spatiotemporal Learning for Online Modeling of Distributed Parameter SystemsZhi Wang, Han‐Xiong LiIEEE Transactions · City University of Hong Kong
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.