Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

25 papers of 6,984Sort Recent · Most cited
  1. 2024
    Continual Learning in Convolutional Neural Networks with Tensor Rank UpdatesMatt Krol, Rakib Hyder, Michael Peechatt … Panos P. MarkopoulosIEEE 13rd Sensor Array and Multichannel Signal Processing… · Rochester Institute of Technology · University of California, Riverside · +2
  2. 2024
    Continual Learning with Weight InterpolationJędrzej Kozal, Jan Wasilewski, Bartosz Krawczyk, Michał WoźniakCVPR · AGH University of Krakow · Rochester Institute of Technology
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  3. 2023
    Design principles for lifelong learning AI acceleratorsDhireesha Kudithipudi, Anurag Daram, Abdullah M. Zyarah … Benjamin R. EpsteinNature Electronics · The University of Texas at San Antonio · Sandia National Laboratories · +6
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  4. 2023
    How Efficient Are Today’s Continual Learning Algorithms?Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Christopher KananCVPR · Rochester Institute of Technology · University of Rochester
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  5. 2019
    Spiking Neural Predictive Coding for Continual Learning from Data StreamsAlexander G. OrorbiaNeurocomputing · Rochester Institute of Technology
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  6. 2022
    System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy GamesIndranil Sur, Zachary Daniels, Abrar Rahman … Aswin RaghavanInternational Conference on AI-ML-Systems · SRI International · American University · +3
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  7. 2022
    Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative ReplayHitesh Vaidya, Travis Desell, Alexander G. OrorbiaAAAI · Rochester Institute of Technology
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  8. 2022
    Unsupervised Continual Learning for Gradually Varying DomainsAbu Md Niamul Taufique, Chowdhury Sadman Jahan, Andreas SavakisCVPR · Rochester Institute of Technology
  9. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
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  10. 2021
    Replay in Deep Learning: Current Approaches and Missing Biological ElementsTyler L. Hayes, Giri P. Krishnan, Maxim Bazhenov … Christopher KananNeural Computation · Rochester Institute of Technology · University of California San Diego · +5
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  11. 2021
    Avalanche: an End-to-End Library for Continual LearningVincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu … Davide MaltoniCVPR · University of Pisa · University of Bologna · +12
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  12. 2021
    Selective Replay Enhances Learning in Online Continual Analogical ReasoningTyler L. Hayes, Christopher KananCVPR · Rochester Institute of Technology · Cornell University · +1
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  13. 2021
    A Continual Learning Framework for Uncertainty-Aware Interactive Image SegmentationErvine Zheng, Qi Yu, Rui Li … Anne R. HaakeAAAI · Rochester Institute of Technology
  14. 2020
    Metaplasticity in Multistate Memristor Synaptic NetworksFatima Tuz Zohora, Abdullah M. Zyarah, Nicholas Soures, Dhireesha KudithipudiInternational Symposium on Circuits and Systems · The University of Texas at San Antonio · Rochester Institute of Technology
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  15. 2020
    Lifelong Machine Learning with Deep Streaming Linear Discriminant AnalysisTyler L. Hayes, Christopher KananCVPR · Rochester Institute of Technology
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  16. 2020
    Stream-51: Streaming Classification and Novelty Detection from VideosRyne Roady, Tyler L. Hayes, Hitesh Vaidya, Christopher KananCVPR · Rochester Institute of Technology
  17. 2020
    Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed RepresentationsAlexander G. Ororbia, Ankur Mali, C. Lee Giles, Daniel KiferTNNLS · Rochester Institute of Technology · Pennsylvania State University
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  18. 2020
    REMIND Your Neural Network to Prevent Catastrophic ForgettingTyler L. Hayes, Kushal Kafle, Robik Shrestha … Christopher KananECCV · Rochester Institute of Technology · Adobe Systems (United States) · +2
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  19. 2020
    RODEO: Replay for Online Object DetectionManoj Acharya, Tyler L. Hayes, Christopher KananBMVC · Rochester Institute of Technology
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  20. 2019
    Rethinking Continual Learning for Autonomous Agents and RobotsGerman I. Parisi, Christopher KananarXiv · Universität Hamburg · Rochester Institute of Technology
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  21. 2019
    Memory Efficient Experience Replay for Streaming LearningTyler L. Hayes, Nathan D. Cahill, Christopher KananICRA · Rochester Institute of Technology
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  22. 2019
    Task-Based Neuromodulation Architecture for Lifelong LearningAnurag Daram, Dhireesha Kudithipudi, Ángel Yanguas-GilInternational Symposium on Quality Electronic Design (ISQED) · Rochester Institute of Technology · Argonne National Laboratory
  23. 2018
    Clustered Lifelong Learning Via Representative Task SelectionGan Sun, Yang Cong, Yu Kong, Xiaowei XuICDM · University of Chinese Academy of Sciences · Shenyang Institute of Automation · +3
  24. 2018
    New Metrics and Experimental Paradigms for Continual LearningTyler L. Hayes, Ronald Kemker, Nathan D. Cahill, Christopher KananCVPR · Rochester Institute of Technology
  25. 2018
    Measuring Catastrophic Forgetting in Neural NetworksRonald Kemker, Marc McClure, Angelina Abitino … Christopher KananAAAI · Rochester Institute of Technology · Swarthmore College
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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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.