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.

27 papers of 11,817Sort Recent · Most cited
  1. 2021
    Generative feature-driven image replay for continual learningKevin Thandiackal, Tiziano Portenier, Andrea Giovannini … Orçun GökselImage and Vision Computing · ETH Zurich · IBM Research - Zurich · +1
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  2. 2022
    Bio-inspired, task-free continual learning through activity regularizationFrancesco Lässig, Pau Vilimelis Aceituno, Martino Sorbaro, Benjamin F. GreweBiological Cybernetics · SIB Swiss Institute of Bioinformatics · University of Zurich · +2
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  3. 2022
    Biologically-Inspired Continual Learning of Human Motion SequencesJ. C. Ott, Shih‐Chii LiuICASSP · SIB Swiss Institute of Bioinformatics · University of Zurich · +1
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  4. 2022
    Fast Hierarchical Learning for Few-Shot Object DetectionYihang She, Goutam Bhat, Martin Danelljan, Fisher YuIROS · ETH Zurich
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  5. 2022
    In-memory Realization of In-situ Few-shot Continual Learning with a Dynamically Evolving Explicit MemoryGeethan Karunaratne, Michael Hersche, J. Langeneager … Abbas RahimiESSCIRC 2022- IEEE 48th European Solid State Circuits Con… · ETH Zurich · IBM Research - Zurich · +2
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  6. 2021
    Continual Adaptation of Semantic Segmentation Using Complementary 2D-3D Data RepresentationsJonas Frey, Hermann Blum, Francesco Milano … César CadenaRA-L · ETH Zurich
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  7. 2022
    Operative dimensions in unconstrained connectivity of recurrent neural networksRenate Krause, Matthew Cook, Sepp Kollmorgen … Giacomo IndiveribioRxiv · SIB Swiss Institute of Bioinformatics · University of Zurich · +1
  8. 2022
    Continual Test-Time Domain AdaptationQin Wang, Olga Fink, Luc Van Gool, Dengxin DaiCVPR · ETH Zurich · École Polytechnique Fédérale de Lausanne · +1
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  9. 2022
    Constrained Few-shot Class-incremental LearningMichael Hersche, Geethan Karunaratne, Giovanni Cherubini … Abbas RahimiCVPR · ETH Zurich · IBM Research - Zurich
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  10. 2022
    Sound and Visual Representation Learning with Multiple Pretraining TasksArun Balajee Vasudevan, Dengxin Dai, Luc Van GoolCVPR · ETH Zurich · KU Leuven
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  11. 2022
    Continual Attentive Fusion for Incremental Learning in Semantic SegmentationGuanglei Yang, Enrico Fini, Dan Xu … Elisa RicciIEEE Trans. Multimedia · University of Trento · Harbin Institute of Technology · +5
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  12. 2022
    Introducing principles of synaptic integration in the optimization of deep neural networksGiorgia Dellaferrera, Stanisław Woźniak, Giacomo Indiveri … Evangelos EleftheriouNature Communications · University of Zurich · IBM Research - Zurich · +3
  13. 2022
    What Has Been Enhanced in my Knowledge-Enhanced Language Model?Yifan Hou, Guoji Fu, Mrinmaya SachanEMNLP · ETH Zurich · Southern University of Science and Technology
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  14. 2021
    A TinyML Platform for On-Device Continual Learning With Quantized Latent ReplaysLeonardo Ravaglia, Manuele Rusci, Davide Nadalini … Luca BeniniIEEE Journal on Emerging and Selected Topics in Circuits… · University of Bologna · University of Modena and Reggio Emilia · +1
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  15. 2021
    EILE: Efficient Incremental Learning on the EdgeXi Chen, Chang Gao, Tobi Delbrück, Shih‐Chii LiuIEEE 3rd International Conference on Artificial Intellige… · SIB Swiss Institute of Bioinformatics · University of Zurich · +1
  16. 2021
    Presynaptic stochasticity improves energy efficiency and helps alleviate the stability-plasticity dilemmaSimon Schug, Frederik Benzing, Angelika StegerbioRxiv · SIB Swiss Institute of Bioinformatics · University of Zurich · +1
  17. 2020
    Memory-Latency-Accuracy Trade-Offs for Continual Learning on a RISC-V Extreme-Edge NodeLeonardo Ravaglia, Manuele Rusci, Alessandro Capotondi … Luca BeniniIEEE Workshop on Signal Processing Systems · University of Bologna · University of Modena and Reggio Emilia · +1
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  18. 2020
    Continual Learning in Recurrent Neural Networks with HypernetworksBenjamin Ehret, Christian Henning, Maria R. Cervera … Benjamin F. GrewearXiv · ETH Zurich
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  19. 2020
    Coresets via Bilevel Optimization for Continual Learning and StreamingZalán Borsos, Mojmír Mutný, Andreas KrauseNeurIPS · ETH Zurich
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  20. 2020
    Reparameterizing Convolutions for Incremental Multi-Task Learning without Task InterferenceMenelaos Kanakis, David Brüggemann, Suman Saha … Luc Van GoolSpringer LNCS · ETH Zurich · KU Leuven
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  21. 2019
    Incremental Learning of Hand Symbols Using Event-Based CamerasIulia Alexandra Lungu, Shih‐Chii Liu, Tobi DelbrückIEEE Journal on Emerging and Selected Topics in Circuits… · University of Zurich · ETH Zurich
  22. 2019
    Incremental Learning Meets Reduced Precision NetworksYuhuang Hu, Tobi Delbrück, Shih‐Chii LiuIEEE International Symposium on Circuits and Systems (ISCAS) · SIB Swiss Institute of Bioinformatics · University of Zurich · +1
  23. 2019
    Parameter Uncertainty for End-to-end Speech RecognitionStefan Braun, Shih‐Chii LiuICASSP · SIB Swiss Institute of Bioinformatics · University of Zurich · +1
  24. 2019
    Fast event-driven incremental learning of hand symbolsIulia Alexandra Lungu, Shih‐Chii Liu, Tobi DelbrückIEEE International Conference on Artificial Intelligence… · SIB Swiss Institute of Bioinformatics · University of Zurich · +1
  25. 2018
    Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell OrdersTian Guo, Albert Bifet, Nino Antulov-FantulinIEEE Conference Proceedings · ETH Zurich · Télécom Paris
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  26. 2018
    A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and ProtocolsNeerav Karani, Krishna Chaitanya, Christian F. Baumgartner, Ender KonukoğluSpringer LNCS · ETH Zurich
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  27. 2018
    Learn the new, keep the old: Extending pretrained models with new anatomy and imagesFırat Özdemir, Philipp Fuernstahl, Orçun GökselSpringer LNCS · ETH Zurich · University of Zurich · +1
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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.