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.

19 papers of 11,817Sort Recent · Most cited
  1. 2022
    MEIL-NeRF: Memory-Efficient Incremental Learning of Neural Radiance FieldsJaeyoung Chung, K. Lee, Sungyong Baik, Kyoung Mu LeeIEEE Access · Seoul National University · Hanyang University
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  2. 2022
    Rebalancing Batch Normalization for Exemplar-Based Class-Incremental LearningSungmin Cha, Sungjun Cho, Dasol Hwang … Taesup MoonCVPR · Seoul National University · University of Illinois Chicago
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  3. 2022
    Brain-inspired Predictive Coding Improves the Performance of Machine Challenging TasksJangho Lee, Jeonghee Jo, Byoung-Hwa Lee … Sungroh YoonFrontiers · Seoul National University · Electronics and Telecommunications Research Institute · +1
  4. 2022
    Class-Incremental Learning by Knowledge Distillation with Adaptive Feature ConsolidationMinsoo Kang, Jaeyoo Park, Bohyung HanCVPR · Seoul National University
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  5. 2022
    Online Continual Learning on a Contaminated Data Stream with Blurry Task BoundariesJihwan Bang, Hyunseo Koh, Seulki Park … Jonghyun ChoiCVPR · NAVER Cloud (South Korea) · Naver (South Korea) · +2
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  6. 2020
    SS-IL: Separated Softmax for Incremental LearningHongjoon Ahn, Jihwan Kwak, Subin Lim … Taesup MoonICCV · Sungkyunkwan University · Seoul National University
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  7. 2021
    Class-Incremental Learning for Action Recognition in VideosJaeyoo Park, Minsoo Kang, Bohyung HanICCV · Seoul National University
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  8. 2021
    Continual Learning on Noisy Data Streams via Self-Purified ReplayChris Dongjoo Kim, Jinseo Jeong, Sangwoo Moon, Gunhee KimICCV · Seoul National University
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  9. 2021
    SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental LearningSungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup MoonNeurIPS · Sungkyunkwan University · Naver (South Korea) · +1
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  10. 2021
    Homeostasis-Inspired Continual Learning: Learning to Control Structural RegularizationJoonyoung Kim, Hyowoon Seo, Wan Choi, Kyomin JungIEEE Access · Seoul National University · University of Oulu · +1
  11. 2018
    StackNet: Stacking feature maps for Continual learningKim Jangho, Jeesoo Kim, Nojun KwakCVPR · Seoul National University
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  12. 2020
    Imbalanced Continual Learning with Partitioning Reservoir SamplingChris Dongjoo Kim, Jinseo Jeong, Gunhee KimSpringer LNCS · Seoul National University
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  13. 2019
    Continual Learning by Asymmetric Loss Approximation With Single-Side OverestimationDong-Min Park, Seokil Hong, Bohyung Han, Kyoung Mu LeeICCV · Seoul National University · Samsung (South Korea)
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  14. 2019
    Autoencoder-Based Incremental Class Learning without Retraining on Old DataEuntae Choi, Kyungmi Lee, Ki‐Young ChoiarXiv · Seoul National University · Massachusetts Institute of Technology
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  15. 2018
    Lifelong Learning with the Feedback-loop between Emotions and Actions via Internal RewardDharani Punithan, Byoung‐Tak ZhangProcedia Computer Science · Seoul National University
  16. 2017
    Continual Learning with Deep Generative ReplayHanul Shin, Jung Kwon Lee, Jaehong Kim, Jiwon KimNeurIPS · Seoul National University · Samsung (South Korea)
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  17. 2017
    Overcoming Catastrophic Forgetting by Incremental Moment MatchingSang-Woo Lee, Jin-Hwa Kim, Jae-Hyun Jun … Byoung‐Tak ZhangNeurIPS · Seoul National University · Naver (South Korea)
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  18. 2015
    Dual Memory Architectures for Fast Deep Learning of Stream Data via an Online-Incremental-Transfer StrategySang-Woo Lee, Min-Oh Heo, Jiwon Kim … Byoung‐Tak ZhangarXiv · Seoul National University
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  19. 2015
    Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon VideosJung-Woo Ha, Kyung-Min Kim, Byoung‐Tak ZhangAAAI · Seoul National 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.