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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.

231 papers of 8,653 · showing 151–200Sort Recent · Most cited
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  1. 2018
    Continual Learning Through Expandable Elastic Weight ConsolidationAndrew Jones, Nathan SpraguePreprint
  2. 2018
    Overcoming Catastrophic Forgetting in Neural Machine TranslationGregory KellPreprint
  3. 2018
    Incremental Segmentation on Private Data without Catastrophic ForgettingTao Hu, PekingPreprint
  4. 2018
    3 Our Proposal : Reinforced Continual LearningJu XuPreprint
  5. 2018
    Developing Toward Generality : Overcoming Catastrophic Forgetting with Developmental CompressionShawn BeaulieuPreprint
  6. 2018
    Developing Toward Generality: Combating Catastrophic Forgetting with Developmental CompressionShawn BeaulieuPreprint
  7. 2018
    Exemplar-Supported Generative Reproduction for Class Incremental Learning Supplementary MaterialChen HePreprint
  8. 2018
    Generative Adversarial Networks and Continual Learning ∗Kevin J Liang, Chunyuan Li, Guoyin Wang, L. CarinPreprint
  9. 2018
    Not-so-Catastrophic Forgetting in Deep Reinforcement Learning on Sequential AtariGiacomo SpiglerPreprint
  10. 2018
    Preventing Catastrophic Forgetting in an Online Learning SettingAyon Borthakur, M. Einhorn, Nikhil DhawanPreprint
  11. 2018
    Tackling Transfer Learning and Catastrophic Forgetting Using Asynchronous Methods for Deep Reinforcement LearningJoao G. RibeiroPreprint
  12. 2018
    Using Deep Learning to create a Universal Game Player Tackling Transfer Learning and Catastrophic Forgetting Using Asynchronous Methods for Deep Reinforcement LearningJoao G. RibeiroPreprint
  13. 2017
    A Proposal of Modularity Enhancement Method to Reduce Catastrophic Forgetting for Neural Network Structuring Linked Open DataLu Chen, M. MurataPreprint
  14. 2017
    Linked Open Dataの構造化のためのニューラルネットワークに対するCatastrophic Forgetting軽減のためのモジュラリティを高める手法の提案Lu Chen, 正幸 村田Preprint
  15. 2017
    Reversible and mergeable learning for continual learning of artificial neural networks = 인공 신경망의 지속 학습을 위한 가역 및 가합 학습J. LeePreprint
  16. 2017
    Supplementary Material : Continual Learning Through Synaptic IntelligenceFriedemann Zenke, Ben Poole, S. GanguliPreprint
  17. 2017
    Variational Continual Learning in Deep ModelsCuong V Nguyen, Yingzhen Li, Thang D. Bui, Richard E. TurnerPreprint
  18. 2016
    Dedicated Memory Models for Continual Learning in the Presence of Concept DriftViktor Losing, B. Hammer, Heiko WersingPreprint
  19. 2016
    Lifelong Machine Learning November , 2016Zhiyuan LiuPreprint
  20. 2015
    Incremental learning of deep neural networks mitigating catastrophic forgettingHyungwon Choi, Jaeyoung Jun, Yunhun Jang … Dae-Shik KimPreprint
  21. 2015
    Incremental Learning in Deep Neural NetworksYuan LiuPreprint
  22. 2015
    The Online Coupon-Collector Problem and Its Application to Lifelong Reinforcement LearningE. Brunskill, Lihong LiPreprint
  23. 2015
    Neuron Clustering for Mitigating Catastrophic Forgetting in Supervised and Reinforcement LearningBenjamin GoodrichPreprint
  24. 2015
    Mitigating Catastrophic Forgetting in Temporal Difference Learning with Function ApproximationBenjamin Goodrich, I. ArelPreprint
  25. 2015
    Incremental learning of action models as HMMs over qualitative trajectory representationsMaximilian Panzner, P. CimianoPreprint
  26. 2015
    Yuan Liu INCREMENTAL LEARNING IN DEEP NEURAL NETWORKSYuan LiuPreprint
  27. 2014
    An incremental learning system for artificial neural networksD. Wet, Anton Petrus ChristiaanPreprint
  28. 2014
    A Neural Network Model for Incremental Learning of Large-Scale Stream DataA. Aminah, Kiminori Fukase, S. OzawaPreprint
  29. 2014
    Scene Interpretation for Lifelong Robot LearningMustafa Ersen, Melodi Deniz Ozturk, Mehmet Biberci … H. YalcinPreprint
  30. 2013
    Spatial Pattern Learning, Catastrophic Forgetting, and Optimal Rules of Synaptic TransmissionDaniel S. Levine, Wesley R. ElsberryPreprint
  31. 2013
    Mitigation of Catastrophic Interference in Neural Networks and Ensembles using a Fixed Expansion LayerRobert CoopPreprint
  32. 2012
    EFFICIENT MULTI-CLASS INCREMENTAL LEARNING USING GAUSSIAN PROCESSESA. Lütz, E. Rodner, Joachim DenzlerPreprint
  33. 2012
    New Multi-label Sample Class Incremental Learning AlgorithmXiu-Kun WangPreprint
  34. 2011
    The Hopfield-type Memory Without Catastrophic ForgettingI. Karandashev, B. Kryzhanovsky, L. LitinskiiPreprint
  35. 2011
    New class incremental learning methodXiu-Kun WangPreprint
  36. 2011
    Fuzzy ARTMAP: A neural network for fast stable incremental learning and seismic event discriminationE. Akhouayri, D. AglizPreprint
  37. 2010
    Catastrophic Forgetting in Reinforcement-Learning EnvironmentsAndrew CahillPreprint
  38. 2010
    Evolving Neural Networks for Improved Incremental Learning PerformanceJ. BullinariaPreprint
  39. 2009
    Avoiding Catastrophic Forgetting by a Dual-Network Memory Model Using a Chaotic Neural NetworkM. HattoriPreprint
  40. 2009
    A Proposal For Continual Learning In RoboticsU. Nehmzow, L. RianoPreprint
  41. 2009
    A Survey of Research Work on Incremental Learning Based on Feedforward Neural NetworksWen-Xian YuPreprint
  42. 2009
    Meaningful Representations Prevent Catastrophic InterferenceJ. Bieger, I. Sprinkhuizen-Kuyper, I. V. van RooijPreprint
  43. 2008
    Study on Class Incremental Learning Algorithm Based on Hyper-sphere Support Vector MachinesChun-Li WangPreprint
  44. 2008
    Associative Memory System for Incremental Learning in Noisy Environment Using Self-Organizing Incremental Neural NetworkA. Sudo, Akihiro Satou, O. HasegawaPreprint
  45. 2008
    Deep Bayesian Neural Networks for Continual LearningSeongho SonPreprint
  46. 2008
    Forget-me-net : Overcoming catastrophic forgetting in backpropagation neural networksAbdallah El Ali, L. Bazen, I. Groen … Kendall RattnerPreprint
  47. 2007
    Art-based Modular Networks for Incremental Learning of Hierarchical Clusterings This Paper Will Appear in a Special Issue of Connection Science on \combining Artiicial Neural Networks". 0 Author InformationG. BartfaiPreprint
  48. 2007
    Study on weighted class-incremental learning algorithm for support vector machinesChun WangPreprint
  49. 2006
    Multi-class Incremental Learning Based on Support Vector MachinesPei YangPreprint
  50. 2006
    Benchmarking Catastrophic Forgetting in Neural NetworksOle-Marius Moe-HelgesenPreprint
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.