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.

6 papers of 11,817Sort Recent · Most cited
  1. 2021
    Recent Advances of Continual Learning in Computer Vision: An OverviewHaoxuan Qu, Hossein Rahmani, Li Xu … Jun LiuIET Computer Vision · Lancaster University · Singapore University of Technology and Design
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  2. 2022
    Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class RepresentationGuangchen Shi, Yirui Wu, Jun Liu … Tong LüACM International Conference on Multimedia · Hohai University · Singapore University of Technology and Design · +3
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  3. 2021
    ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World DataKin Wai Cheuk, Dorien Herremans, Li SuACM International Conference on Multimedia · Singapore University of Technology and Design · Academia Sinica
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  4. 2021
    Else-Net: Elastic Semantic Network for Continual Action Recognition from Skeleton DataTianjiao Li, Qiuhong Ke, Hossein Rahmani … Jun LiuICCV · Singapore University of Technology and Design · The University of Melbourne · +2
  5. 2020
    InfoMax-GAN: Improved Adversarial Image Generation via Information Maximization and Contrastive LearningKwot Sin Lee, Ngoc-Trung Tran, Ngai‐Man CheungWACV · University of Cambridge · Snap (United States) · +1
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  6. 2018
    Self-organizing maps for storage and transfer of knowledge in reinforcement learningThommen George Karimpanal, Roland BouffanaisAdaptive Behavior · Singapore University of Technology and Design
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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.