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 101–150Sort Recent · Most cited
  1. 2019
    Efficient Class-Incremental Learning Based on Bag-of-Sequencelets Model for Activity RecognitionJongwoo Lee, Ki-Sang HongIEICE Transactions on Fundamentals of Electronics Communi… · Pohang University of Science and Technology
  2. 2019
    An Auto-ML Framework Based on GBDT for Lifelong LearningJinlong Chai, Jiangeng Chang, Yakun Zhao, Honggang LiuarXiv · Beijing University of Posts and Telecommunications · Central South University
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  3. 2019
    Learning Continually from Low-shot Data StreamCanyu Le, Xihan Wei, Biao Wang … Chen, ZhongguiarXiv
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  4. 2019
    Collaborative Method for Incremental Learning on Classification and GenerationByungju Kim, Jae-Young Lee, Kyungsu Kim … Junmo KimICIP · Korea Advanced Institute of Science and Technology · Samsung (United States)
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  5. 2019
    Discriminative Features for Incremental Learning ClassifierTin Lay Nwe, Balaji Nataraj, Shudong Xie … Dong ShengICIP · Institute for Infocomm Research · National University of Singapore
  6. 2019
    Adaptive Resonance Theory in the time scales calculusJohn SeifferttNeural Networks · Providence College
  7. 2019
    Online Continual Learning with Maximally Interfered RetrievalRahaf Aljundi, Lucas Caccia, Eugene Belilovsky … Tinne TuytelaarsarXiv · McGill University · Université de Montréal · +1
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  8. 2019
    Continual learning of context-dependent processing in neural networksGuanxiong Zeng, Yang Chen, Bo Cui, Shan YuNature Machine Intelligence · Chinese Academy of Sciences · Institute of Automation · +2
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  9. 2019
    Visualizing the PHATE of Neural NetworksScott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal MishneNeurIPS · Yale University · Princeton University · +1
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  10. 2019
    Toward Understanding Catastrophic Forgetting in Continual LearningCuong V. Nguyen, Alessandro Achille, Michael Lam … Stefano SoattoarXiv
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  11. 2019PDF ↗
  12. 2019
    Biologically inspired sleep algorithm for artificial neural networksGiri P. Krishnan, Timothy Tadros, Ramyaa Ramyaa, Maxim BazhenovarXiv
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  13. 2019
    DynMat, a network that can learn after learningJung H. LeePubMed · Allen Institute for Brain Science · Allen Institute
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  14. 2019PDF ↗
  15. 2019
    A Distributed Class-Incremental Learning Method Based on Neural Network Parameter FusionHongtao Guan, Yijie Wang, Xingkong Ma, Yongmou LiIEEE 21st International Conference on High Performance Co… · National University of Defense Technology
  16. 2019
    Complementary Learning for Overcoming Catastrophic Forgetting Using Experience ReplayMohammad Rostami, Soheil Kolouri, Praveen K. PillyIJCAI · California University of Pennsylvania · University of Pennsylvania · +1
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  17. 2019
    Closed-Loop Memory GAN for Continual LearningAmanda Rios, Laurent IttiIJCAI · University of Southern California · California Southern University
  18. 2019
    Learning Shared Knowledge for Deep Lifelong Learning using Deconvolutional NetworksSeungwon Lee, James Stokes, Eric EatonIJCAI · University of Pennsylvania · Flatiron Health (United States) · +1
  19. 2019
    Extensible Cross-Modal HashingTianyi Chen, Lan Zhang, Shi-cong Zhang … Bai-chuan HuangIJCAI · University of Science and Technology of China · Northeastern University · +1
  20. 2019
    Self-Organizing Incremental Neural Networks for Continual LearningChayut Wiwatcharakoses, Daniel BerrarIJCAI · Tokyo Institute of Technology
  21. 2019
    Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and SustainabilityYang Yang, Da-Wei Zhou, De‐Chuan Zhan … Yuan JiangKDD · Nanjing University · Rutgers, The State University of New Jersey
  22. 2019
    Towards AutoML in the presence of Drift: first resultsJorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales … Michèle SébagIJCAI · National Institute of Astrophysics, Optics and Electronics · Nanjing University · +2
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  23. 2019
    Adaptive Compression-based Lifelong LearningShivangi Srivastava, Maxim Berman, Matthew B. Blaschko, Devis TuiaSocio-Environmental Systems Modeling · Wageningen University & Research · KU Leuven
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  24. 2019
    Application of a Selective Desensitization Neural Network to Concept Drift ProblemsIchiba Tomoki, Kazumasa Horie, Someno Shoichi … Masahiko MoritaJournal of Signal Processing · University of Tsukuba
  25. 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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  26. 2019
    Scalable Recollections for Continual Lifelong LearningMatthew Riemer, Tim Klinger, Djallel Bouneffouf, Michele FranceschiniAAAI
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  27. 2019
    The Utility of Sparse Representations for Control in Reinforcement LearningVincent Liu, Raksha Kumaraswamy, Lei Le, Martha WhiteAAAI · University of Alberta · Indiana University Bloomington
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  28. 2019
    Towards continual reinforcement learning through evolutionary meta-learningDjordje Grbic, Sebastian RisiGenetic and Evolutionary Computation Conference Companion · IT University of Copenhagen
  29. 2019
    Fine-Grained Continual LearningV. Lomonaco, D. Maltoni, Lorenzo PellegriniarXiv
  30. 2019
    Challenges for learning in complex environmentsRaia HadsellGenetic and Evolutionary Computation Conference · Google DeepMind (United Kingdom) · Google (United Kingdom)
  31. 2019
    Rethinking Continual Learning for Autonomous Agents and RobotsGerman I. Parisi, Christopher KananarXiv · Universität Hamburg · Rochester Institute of Technology
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  32. 2019
    Generative Models from the perspective of Continual LearningTimothée Lesort, Hugo Caselles-Dupré, Michael Garcia-Ortiz … David FilliatIEEE International Joint Conference on Neural Network · Institut national de recherche en sciences et technologies du numérique · École Nationale Supérieure de Techniques Avancées · +2
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  33. 2019
    An End-to-End Architecture for Class-Incremental Object Detection with Knowledge DistillationHao Yu, Yanwei Fu, Yu–Gang Jiang, Qi TianIEEE International Conference on Multimedia and Expo (ICME) · Fudan University · Jilian Technology Group (China) · +1
  34. 2019
    A New Knowledge Distillation for Incremental Object DetectionLi Chen, Chunyan Yu, Lvcai ChenIJCNN · Fuzhou University
  35. 2019
    Lifelong Learning in Sensor-Based Human Activity RecognitionJuan Ye, Simon Dobson, Franco ZambonelliIEEE Pervasive Computing · University of St Andrews · University of Modena and Reggio Emilia
  36. 2019
    A Class-Incremental Learning Method Based on One Class Support Vector MachineChengfei Yao, Jie Zou, Yanan Luo … Gang BaiJournal of Physics Conference Series · Nankai University
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  37. 2019
    Effect of Pruning on Catastrophic Forgetting in Growing Dual Memory NetworksWei Shiung Liew, Chu Kiong Loo, Vadym Gryshchuk … Stefan WermterIJCNN · University of Malaya · Universität Hamburg
  38. 2019
    Criteria for Learning without Forgetting in Artificial Neural NetworksRupesh Raj Karn, Prabhakar Kudva, Ibrahim M. ElfadelIEEE International Conference on Cognitive Computing (ICCC) · Khalifa University of Science and Technology · IBM Research - Thomas J. Watson Research Center
  39. 2019
  40. 2019
    Stable Network MorphismTao Wei, Changhu Wang, Chang Wen ChenIJCNN · University at Buffalo, State University of New York · Chinese University of Hong Kong, Shenzhen
  41. 2019
    Interleaved training prevents catastrophic forgetting in spiking neural networksRyan Golden, Jean Erik Delanois, Pavel Šanda, Maxim BazhenovbioRxiv · University of California San Diego · Czech Academy of Sciences · +1
  42. 2019
    Spatial Map Learning with Self-Organizing Adaptive Recurrent Incremental NetworkWei Hong Chin, Naoyuki Kubota, Chu Kiong Loo … Honghai LiuIJCNN · Tokyo Metropolitan University · University of Malaya · +1
  43. 2019
    Selective Hypothesis Transfer for Lifelong LearningDiana Benavides‐Prado, Yun Sing Koh, Patricia RiddleIJCNN · University of Auckland
  44. 2019
    Catastrophic Interference in Disguised Face RecognitionP. B. Ardakani, Diego Velazquez Dorta, J. M. Gonfaus … Jordi GonzàlezIberian Conference on Pattern Recognition and Image Analysis
  45. 2019
    A Spike Time-Dependent Online Learning Algorithm Derived From Biological OlfactionAyon Borthakur, Thomas A. ClelandFrontiers · Cornell University
  46. 2019
    Semi-Unsupervised Lifelong Learning for Sentiment Classification: Less Manual Data Annotation and More Self-StudyingXianbin Hong, Gautam Pal, Sheng-Uei Guan … Xin HuangHPCCT/BDAI · Xi’an Jiaotong-Liverpool University · University of Liverpool
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  47. 2019
    Beneficial perturbation network for continual learningShixian Wen, Laurent IttiarXiv · University of Southern California · California Southern University
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  48. 2019
    Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-CorrectionFengda Zhu, Xiaojun Chang, Runhao Zeng, Mingkui TanarXiv · South China University of Technology
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  49. 2019PDF ↗
  50. 2019
    Scalable and Order-robust Continual Learning with Hierarchically Decomposed Networks.J. Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz … Guillaume DesjardinsPreprint
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.