Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

240 papers of 4,574 · showing 101–150Sort Recent · Most cited
  1. 2020
    Neural Topic Modeling with Continual Lifelong LearningPankaj Gupta, Yatin Chaudhary, Thomas A. Runkler, Schütze, HinrichICML · Siemens (Germany) · Technical University of Munich · +2
    PDF ↗
  2. 2020
    Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian ProcessesMengdi Xu, Wenhao Ding, Jiacheng Zhu … Ding ZhaoNeurIPS · Carnegie Mellon University · Tsinghua University · +1
    PDF ↗
  3. 2020
    SOLA: Continual Learning with Second-Order Loss ApproximationDong Yin, Mehrdad Farajtabar, Ang Li … A. MottarXiv
    PDF ↗
  4. 2020PDF ↗
  5. 2020
    Learning to Learn with Feedback and Local PlasticityJack Lindsey, Ashok Litwin-KumarNeurIPS · Columbia University
    PDF ↗
  6. 2020
    GAN Memory with No ForgettingYulai Cong, Miaoyun Zhao, Jianqiao Li … Lawrence CarinNeurIPS · Duke University
    PDF ↗
  7. 2020
    Understanding the Role of Training Regimes in Continual LearningSeyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, Hassan GhasemzadehNeurIPS
    PDF ↗
  8. 2020
    Learning Causal Models OnlineKhurram Javed, Martha White, Yoshua BengioarXiv
    PDF ↗
  9. 2020
    BI-MAML: Balanced Incremental Approach for Meta LearningYang Zheng, Jinlin Xiang, Kun Su, Eli ShlizermanarXiv
    PDF ↗
  10. 2020
    Collaborative and continual learning for classification tasks in a society of devicesFernando E. Casado, Dylan Lema, Roberto Iglesias … Senén BarroarXiv
    PDF ↗
  11. 2020
    Move-to-Data: A new Continual Learning approach with Deep CNNs, Application for image-class recognitionMiltiadis Poursanidis, Jenny Benois‐Pineau, Akka Zemmari … Aymar de RugyarXiv · Laboratoire Bordelais de Recherche en Informatique · Institut de Neurosciences Cognitives et Intégratives d’Aquitaine
    PDF ↗
  12. 2020
    Understanding Regularisation Methods for Continual LearningFrederik BenzingarXiv · École Polytechnique Fédérale de Lausanne
    PDF ↗
  13. 2020
    Self-Supervised Learning Aided Class-Incremental Lifelong LearningSong Zhang, Gehui Shen, Huang, Jinsong, Deng, Zhi-HongarXiv · Peking University
    PDF ↗
  14. 2020
    Gaussian Gated Linear NetworksDavid Budden, Adam Marblestone, Eren Sezener … Joel VenessNeurIPS · Google (United States)
    PDF ↗
  15. 2020
    Optimal Continual Learning has Perfect Memory and is NP-hardJeremias Knoblauch, Hisham Husain, Tom DietheICML · University of Warwick · The Alan Turing Institute · +2
    PDF ↗
  16. 2020
    Coresets via Bilevel Optimization for Continual Learning and StreamingZalán Borsos, Mojmír Mutný, Andreas KrauseNeurIPS · ETH Zurich
    PDF ↗
  17. 2020
    Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversionHongxu Yin, Pavlo Molchanov, Jose M. Álvarez … Jan KautzCVPR · Princeton University · University of Illinois Urbana-Champaign
    PDF ↗
  18. 2020
    Maintaining Discrimination and Fairness in Class Incremental LearningBowen Zhao, Xi Xiao, Guojun Gan … Shu‐Tao XiaCVPR · Peng Cheng Laboratory · Tsinghua University
    PDF ↗
  19. 2020
    Few-Shot Class-Incremental LearningXiaoyu Tao, Xiaopeng Hong, Xinyuan Chang … Yihong GongCVPR · Xi'an Jiaotong University · Peng Cheng Laboratory
    PDF ↗
  20. 2020
    Semantic Drift Compensation for Class-Incremental LearningLu Yu, Bartłomiej Twardowski, Xialei Liu … Joost van de WeijerCVPR · Universitat Autònoma de Barcelona · Northwestern Polytechnical University · +1
    PDF ↗
  21. 2020
    Mnemonics Training: Multi-Class Incremental Learning Without ForgettingYaoyao Liu, Yuting Su, An-An Liu … Qianru SunCVPR · Tianjin University · Max Planck Institute for Informatics · +1
    PDF ↗
  22. 2020
    Modeling the Background for Incremental Learning in Semantic SegmentationFabio Cermelli, Massimiliano Mancini, Samuel Rota Bulò … Barbara CaputoCVPR · Politecnico di Torino · Italian Institute of Technology · +3
    PDF ↗
  23. 2020
    Incremental Few-Shot Object DetectionJuan-Manuel Pérez-Rúa, Xiatian Zhu, Timothy M. Hospedales, Tao XiangCVPR · Samsung (United Kingdom) · University of Edinburgh · +1
    PDF ↗
  24. 2020
    Conditional Channel Gated Networks for Task-Aware Continual LearningDavide Abati, Jakub M. Tomczak, Tijmen Blankevoort … Babak Ehteshami BejnordiCVPR · University of Modena and Reggio Emilia
    PDF ↗
  25. 2020
    Generative Feature Replay For Class-Incremental LearningXialei Liu, Chenshen Wu, Mikel Menta … Joost van de WeijerCVPR · Universitat Autònoma de Barcelona · University of Florence · +1
    PDF ↗
  26. 2020
    Incremental Learning in Online ScenarioJiangpeng He, Runyu Mao, Zeman Shao, Fengqing ZhuCVPR · Purdue University West Lafayette
    PDF ↗
  27. 2020
    Lifelong Machine Learning with Deep Streaming Linear Discriminant AnalysisTyler L. Hayes, Christopher KananCVPR · Rochester Institute of Technology
    PDF ↗
  28. 2020
    iTAML: An Incremental Task-Agnostic Meta-learning ApproachJathushan Rajasegaran, Salman Khan, Munawar Hayat … Mubarak ShahCVPR · Inception Institute of Artificial Intelligence · Linköping University · +1
    PDF ↗
  29. 2020
    Continual Learning for Anomaly Detection in Surveillance VideosKeval Doshi, Yasin YılmazCVPR · University of South Florida
    PDF ↗
  30. 2020
    Learning to Segment the TailXinting Hu, Yi Jiang, Kaihua Tang … Hanwang ZhangCVPR · Nanyang Technological University · Alibaba Group (United States) · +1
    PDF ↗
  31. 2020
    Rehearsal-Free Continual Learning over Small Non-I.I.D. BatchesVincenzo Lomonaco, Davide Maltoni, Lorenzo PellegriniCVPR · University of Bologna
    PDF ↗
  32. 2020
    Continual Learning With Extended Kronecker-Factored Approximate CurvatureJanghyeon Lee, Hyeong Gwon Hong, Donggyu Joo, Junmo KimCVPR · Korea Advanced Institute of Science and Technology
    PDF ↗
  33. 2020
    Cognitively-Inspired Model for Incremental Learning Using a Few ExamplesAli Ayub, Alan R. WagnerCVPR · Pennsylvania State University
    PDF ↗
  34. 2020
    Dropout as an Implicit Gating Mechanism For Continual LearningSeyed Iman Mirzadeh, Mehrdad Farajtabar, Hassan GhasemzadehCVPR · Washington State University · Google (United States)
    PDF ↗
  35. 2020
    Reducing catastrophic forgetting with learning on synthetic dataWojciech Masarczyk, Ivona TautkutėCVPR · Warsaw University of Technology · Institute of Theoretical and Applied Informatics · +3
    PDF ↗
  36. 2020
    Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open ProblemMatthias De Lange, Xu Jia, Sarah Parisot … Tinne TuytelaarsCVPR · KU Leuven · Huawei Technologies (Sweden)
    PDF ↗
  37. 2020
    Sequential Mastery of Multiple Visual Tasks: Networks Naturally Learn to Learn and Forget to ForgetGuy Davidson, Michael C. MozerCVPR · Supélec · University of Applied Sciences and Arts of Southern Switzerland · +2
    PDF ↗
  38. 2020
    IROS 2019 Lifelong Robotic Vision: Object Recognition Challenge [Competitions]Heechul Bae, Eoin Brophy, Rosa H. M. Chan … Liguang ZhouIEEE Robotics & Automation Magazine · Electronics and Telecommunications Research Institute · Dublin City University · +9
    PDF ↗
  39. 2020
    StackNet: Stacking feature maps for Continual learningKim Jangho, Jeesoo Kim, Nojun KwakCVPR · Seoul National University
    PDF ↗
  40. 2020
    Continual Learning of Object InstancesKishan Parshotam, Mert KilickayaCVPR · University of Amsterdam
    PDF ↗
  41. 2020
    Progressive growing of self-organized hierarchical representations for explorationMayalen Etcheverry, Pierre‐Yves Oudeyer, Chris ReinkearXiv
    PDF ↗
  42. 2020
    Towards Knowledgeable Supervised Lifelong Learning SystemsDiana Benavides‐Prado, Yun Sing Koh, Patricia RiddleJournal of Artificial Intelligence Research · University of Auckland
    PDF ↗
  43. 2020
    Continual Learning Using Task Conditional Neural NetworksHaoyu Li, Payam Barnaghi, Shirin Enshaeifar, Frieder GanzarXiv
    PDF ↗
  44. 2020
    Improving Performance in Reinforcement Learning by Breaking Generalization in Neural NetworksSina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam WhiteAdaptive Agents and Multi-Agents Systems · University of Alberta
    PDF ↗
  45. 2020
    Visually Grounded Continual Learning of Compositional SemanticsXisen Jin, Junyi Du, Arka Sadhu … Xiang RenarXiv · University of Southern California · California Southern University
    PDF ↗
  46. 2020
    OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep LearningQi She, Fan Feng, Xinyue Hao … Rosa H. M. ChanICRA · City University of Hong Kong · Tsinghua University · +4
    PDF ↗
  47. 2020
    Sequential Presentation Protects Working Memory From Catastrophic InterferenceAnsgar D. Endress, Szilárd SzabóCognitive Science · City, University of London · Budapest University of Technology and Economics
    PDF ↗
  48. 2020
    Bio-Inspired Techniques in a Fully Digital Approach for Lifelong LearningS. Bianchi, Irene Muñoz-Martín, Daniele IelminiFrontiers · Politecnico di Milano
    PDF ↗
  49. 2020
    Continual Deep Learning by Functional Regularisation of Memorable PastPingbo Pan, Siddharth Swaroop, Alexander Immer … Mohammad Emtiyaz KhanNeurIPS
    PDF ↗
  50. 2020
    Exploring Fine-tuning Techniques for Pre-trained Cross-lingual Models via Continual LearningZihan Liu, Genta Indra Winata, Andrea Madotto, Pascale FungarXiv · Hong Kong University of Science and Technology
    PDF ↗
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, and only papers with a PDF we can point you at, so every title opens the paper itself. 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.