Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

319 papers of 8,653 · showing 1–50Sort Recent · Most cited
  1. 2019
    Spiking Neural Predictive Coding for Continual Learning from Data StreamsAlexander G. OrorbiaNeurocomputing · Rochester Institute of Technology
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  2. 2019
    Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set RecognitionMartin Mundt, Iuliia Pliushch, Sagnik Majumder … Visvanathan RameshJournal of Imaging · Goethe University Frankfurt · The University of Texas at Austin · +1
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  3. 2019
    Lifelong Neural Predictive Coding: Learning Cumulatively Online without ForgettingAlex Ororbia, Ankur Mali, C Lee Giles, Daniel KiferNeurIPS
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  4. 2019
    SpaRCe: Improved Learning of Reservoir Computing Systems Through Sparse RepresentationsLuca Manneschi, Andrew C. Lin, Eleni VasilakiTNNLS · University of Sheffield
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  5. 2019
    Overcoming Long-Term Catastrophic Forgetting Through Adversarial Neural Pruning and Synaptic ConsolidationJian Peng, Bo Tang, Hao Jiang … Haifeng LiTNNLS · Central South University · Mississippi State University · +3
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  6. 2019
    A Continual Learning Survey: Defying Forgetting in Classification TasksMatthias Delange, Rahaf Aljundi, Marc Masana … Tinne TuytelaarsTPAMI · Computer Vision Center · Huawei Technologies (Canada)
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  7. 2019
    Representative Task Self-Selection for Flexible Clustered Lifelong LearningGan Sun, Yang Cong, Qianqian Wang … Yun FuTNNLS · Northeastern University · Shenyang Institute of Automation · +3
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  8. 2019
    Better Knowledge Retention through Metric LearningKe Li, Shichong Peng, Kailas Vodrahalli, Jitendra MalikarXiv
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  9. 2019PDF ↗
  10. 2019
    Side-Tuning: Network Adaptation via Additive Side NetworksJeffrey O. Zhang, Alexander F. Sax, Amir Zamir … Jitendra MalikarXiv
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  11. 2019
    Incremental Learning in Deep Convolutional Neural Networks Using Partial Network SharingSyed Shakib Sarwar, Aayush Ankit, Kaushik RoyIEEE Access · Purdue University West Lafayette
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  12. 2019
    Continual learning for image classification. (Apprentissage continu pour la classification des images)Anuvabh DuttUniversité Grenoble Alpes (ComUE) · Université Grenoble Alpes
  13. 2019PDF ↗
  14. 2019
    Continual Learning for RoboticsTimothée Lesort, Vincenzo Lomonaco, Andrei Stoian … Natalia Díaz-RodríguezInformation Fusion · Thales (Portugal) · Institut national de recherche en sciences et technologies du numérique · +3
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  15. 2019
    Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement LearningJoão G. Ribeiro, Francisco S. Melo, João DiasEPiC series in computing · Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento
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  16. 2019
    Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic Information BalancingMohammed Amer, Tomás MaularXiv · University of Nottingham Malaysia Campus
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  17. 2019PDF ↗
  18. 2019
    Learning Sparse Representations Incrementally in Deep Reinforcement LearningJ. Fernando Hernandez-Garcia, Richard S. SuttonarXiv · University of Alberta
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  19. 2019
    Random Path Selection for Continual LearningJathushan Rajasegaran, Munawar Hayat, Salman Hameed Khan … Ling ShaoNeurIPS
  20. 2019
    Bayesian Structure Adaptation for Continual LearningAbhishek Kumar, Sunabha Chatterjee, Piyush RaiarXiv · Indian Institute of Technology Kanpur
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  21. 2019
    Nonparametric Bayesian Structure Adaptation for Continual LearningAbhishek Kumar, Sunabha Chatterjee, Piyush RaiarXiv
  22. 2019
    Regularization Shortcomings for Continual LearningTimothée Lesort, Andrei Stoian, Filliat, DavidarXiv · École d'Ingénieurs en Chimie et Sciences du Numérique · Thales (Portugal)
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  23. 2019
    Indian Buffet Neural Networks for Continual LearningSamuel Kessler, Vu Nguyen, S. Zohren, Stephen J. RobertsarXiv
  24. 2019
    Overcoming Catastrophic Forgetting by Generative RegularizationPatrick H. Chen, Wei Wei, Cho-Jui Hsieh, Bo DaiarXiv
  25. 2019
    Incremental Learning of an Open-Ended Collaborative Skill LibraryDorothea Koert, Susanne Trick, Marco Ewerton … Jan PetersInternational Journal of Humanoid Robotics · Technische Universität Darmstadt · Max Planck Institute for Intelligent Systems
  26. 2019
    Incremental learning for the detection and classification of GAN-generated imagesFrancesco Marra, Cristiano Saltori, Giulia Boato, Luisa VerdolivaInternational Workshop on Information Forensics and Security · Federico II University Hospital · University of Trento
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  27. 2019
    Single-Net Continual Learning with Progressive Segmented TrainingXiaocong Du, Gouranga Charan, Frank Liu, Yu CaoICML · Arizona State University · Oak Ridge National Laboratory
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  28. 2019
    DCIGAN: A Distributed Class-Incremental Learning Method Based on Generative Adversarial NetworksHongtao Guan, Yijie Wang, Xingkong Ma, Yongmou LiIEEE Intl Conf on Parallel & Distributed Processing w… · National University of Defense Technology
  29. 2019
    Frosting Weights for Better Continual TrainingXiaofeng Zhu, Feng Liu, Goce Trajcevski, Dingding WangICML · Northwestern University · Florida Atlantic University · +1
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  30. 2019
    AutoML @ NeurIPS 2018 challenge: Design and ResultsHugo Jair Escalante, Wei-Wei Tu, Isabelle Guyon … Qiang YangMachine Learning · Gleason (United States) · National Institute of Astrophysics, Optics and Electronics · +8
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  31. 2019
    Challenges in Task Incremental Learning for Assistive RoboticsFan Feng, Rosa H. M. Chan, Xuesong Shi … Qi SheIEEE Access · City University of Hong Kong
  32. 2019
    Self-directed Lifelong Learning for Robot VisionTanner Schmidt, Dieter FoxSpringer · Allen Institute
  33. 2019
    GRIm-RePR: Prioritising Generating Important Features for Pseudo-RehearsalC. Atkinson, Brendan McCane, Lech Szymanski, Anthony RobinsarXiv
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  34. 2019
    Machine learning for streaming data: state of the art, challenges, and opportunitiesHeitor Murilo Gomes, Jesse Read, Albert Bifet … João GamaACM SIGKDD Explorations Newsletter · École Polytechnique · Universidade do Porto
  35. 2019
    A Unified Framework for Lifelong Learning in Deep Neural NetworksCharles X. Ling, Tanner BohnarXiv · Western University
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  36. 2019
    Online Learned Continual Compression with Stacked Quantization ModuleLucas Caccia, Eugene Belilovsky, M. Caccia, Joëlle PineauarXiv · McGill University · Meta (Israel)
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  37. 2019PDF ↗
  38. 2019
    Lifelong Learning in Costly Feature SpacesMaria-Florina Balcan, Avrim Blum, Vaishnavh NagarajanTheoretical Computer Science · Carnegie Mellon University · Toyota Technological Institute at Chicago
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  39. 2019
    RILOD: near real-time incremental learning for object detection at the edgeDawei Li, Şerafettin Taşcı, Shalini Ghosh … Larry HeckACM/IEEE Symposium on Edge Computing · Samsung (United States) · Research!America (United States) · +2
  40. 2019
    Task-adaptive incremental learning for intelligent edge devicesZhuwei Qin, Fuxun Yu, Xiang ChenACM/IEEE Symposium on Edge Computing · George Mason University
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  41. 2019
    Automatic Construction of Multi-layer Perceptron Network from Streaming ExamplesMahardhika Pratama, Choiru Za’in, Andri Ashfahani … Weiping DingCIKM · Nanyang Technological University · La Trobe University · +1
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  42. 2019
    SOINN+, a Self-Organizing Incremental Neural Network for Unsupervised Learning from Noisy Data StreamsChayut Wiwatcharakoses, Daniel BerrarExpert Systems with Applications · Tokyo Institute of Technology
  43. 2019
    Continual Learning in a Multi-Layer Network of an Electric FishSalomon Z. Muller, Abigail N Zadina, L. F. Abbott, Nathaniel B. SawtellCell · Columbia University
  44. 2019
    MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream ClassificationMonidipa Das, Mahardhika Pratama, Septiviana Savitri, Jie ZhangICDM · Nanyang Technological University
  45. 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
  46. 2019
  47. 2019
    Variational Policy Chaining for Lifelong Reinforcement LearningChris Doyle, Maxime Guériau, Ivana DusparićIEEE 31st International Conference on Tools with Artifici… · Trinity College Dublin
  48. 2019
    Primitives Generation Policy Learning without Catastrophic Forgetting for Robotic ManipulationFangzhou Xiong, Zhiyong Liu, Kaizhu Huang … Amir HussainICDM · Shandong Institute of Automation · University of Chinese Academy of Sciences · +4
  49. 2019
    Continual Unsupervised Representation LearningDushyant Rao, Francesco Visin, Andrei Rusu … Raia HadsellNeurIPS · Carnegie Mellon University · Google (United States) · +2
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  50. 2019
    Continual Multi-task Gaussian ProcessesPablo Moreno-Muñoz, Antonio Artés-Rodrı́guez, Mauricio A. ÁlvarezarXiv · Universidad Carlos III de Madrid · University of Sheffield
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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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.