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.

187 papers of 8,653 · showing 51–100Sort Recent · Most cited
  1. 2018
    On the role of neurogenesis in overcoming catastrophic forgettingGerman I. Parisi, Xu Ji, Stefan WermterarXiv
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  2. 2018
    Closed-Loop GAN for continual LearningAmanda Rios, Laurent IttiarXiv · University of Southern California · California Southern University
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  3. 2018
    Robust Lifelong Multi-task Multi-view Representation LearningGan Sun, Yang Cong, Jun Li, Yun FuIEEE International Conference on Big Knowledge (ICBK) · University of Chinese Academy of Sciences · Shenyang Institute of Automation · +2
  4. 2018
    Imbalanced Augmented Class Learning with Unlabeled Data by Label Confidence PropagationSiyu Ding, Xuying Liu, Min-Ling ZhangICDM · Southeast University
  5. 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
  6. 2018
    Trends and Challenges in Lifelong Machine Learning Topic ModelsMuhammad Taimoor Khan, Shehzad KhalidInternational Conference on Computing, Electronic and Ele… · National University of Computer and Emerging Sciences · Laboratoire d'Informatique de Paris-Nord · +1
  7. 2018
    Don't forget, there is more than forgetting: new metrics for Continual LearningNatalia Díaz-Rodríguez, Vincenzo Lomonaco, David Filliat, Davide MaltoniarXiv · Laboratoire d’Informatique et Systèmes · University of Bologna
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  8. 2018
    Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong BaselinesYen-Chang Hsu, Yen‐Cheng Liu, Ramasamy, Anita, Kira, ZsoltarXiv · Georgia Institute of Technology
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  9. 2018
    Learning to Learn without Forgetting By Maximizing Transfer and Minimizing InterferenceMatthew Riemer, Ignacio Cases, Robert Ajemian … Gerald TesauroICLR · IBM (United States) · Stanford University · +2
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  10. 2018
    Self-Supervised GAN to Counter ForgettingTing Chen, Xiaohua Zhai, Neil HoulsbyarXiv
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  11. 2018
    Continual Classification Learning Using Generative ModelsFrantzeska Lavda, Jason Ramapuram, Magda Gregorová, Alexandros KalousisNeurIPS
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  12. 2018PDF ↗
  13. 2018
    Incremental Learning for Classification of Unstructured Data Using Extreme Learning MachineSathya Madhusudhanan, Suresh Jaganathan, L. S. JayashreeAlgorithms · Sri Sivasubramaniya Nadar College of Engineering · PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH
  14. 2018
    Comparing continual task learning in minds and machinesTimo Flesch, Jan Balaguer, Ronald Dekker … Christopher SummerfieldPNAS · University of Oxford · Google DeepMind (United Kingdom)
  15. 2018
    Life-long Cross-media Correlation LearningJinwei Qi, Yuxin Peng, Yunkan ZhuoACM international conference on Multimedia · Peking University
  16. 2018
    Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilizationNicolas Y. Masse, Gregory D. Grant, David J. FreedmanPNAS · University of Chicago
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  17. 2018
    Continual State Representation Learning for Reinforcement Learning using Generative ReplayHugo Caselles-Dupré, M. Ortíz, David FilliatarXiv · Laboratoire d’Informatique et Systèmes · SoftBank Robotics (France)
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  18. 2018
    A Neural Model of Schemas and Memory ConsolidationTiffany Hwu, Jeffrey L. KrichmarbioRxiv · University of California, Irvine
  19. 2018
    An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial ExpressionsHenrique Siqueira, Pablo Barros, Sven Magg, Stefan WermterIROS · Universität Hamburg · Hamburg University of Technology
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  20. 2018
    Accelerating Learning in Constructive Predictive Frameworks with the Successor RepresentationCraig Sherstan, Marlos C. Machado, Patrick M. PilarskiIROS · University of Alberta
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  21. 2018
    Incremental Learning-Based Adaptive Object Recognition for Mobile RobotsMehmet Özgür Türkoglu, Frank B. ter Haar, Nanda van der StapIROS · University of Twente
  22. 2018
    Stepwise PathNet: Transfer Learning Algorithm to Improve Network Structure VersatilityShunsuke Imai, Hajime NobuharaIEEE International Conference on Systems, Man, and Cybern… · University of Tsukuba
  23. 2018
    Generative replay with feedback connections as a general strategy for continual learningGido M. van de Ven, Andreas S. ToliasarXiv · Baylor College of Medicine
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  24. 2018
  25. 2018
  26. 2018
    Interpretable Continual LearningTameem Adel, C. Nguyen, Richard E. Turner … Adrian WellerPreprint
  27. 2018
    Learning to remember: Dynamic Generative Memory for Continual LearningOleksiy Ostapenko, M. Puscas, T. Klein, Moin NabiPreprint
  28. 2018
  29. 2018
    Continual Learning via Explicit Structure LearningXilai Li, Yingbo Zhou, Tianfu Wu … Caiming XiongPreprint
  30. 2018
  31. 2018
    Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data StreamsMahardhika Pratama, Andri Ashfahani, Yew-Soon Ong … Edwin LughoferarXiv
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  32. 2018
    StackNet: Stacking Parameters for Continual learningJangho Kim, Jeesoo Kim, Nojun KwakPreprint
  33. 2018
  34. 2018PDF ↗
  35. 2018
    Developmental Reinforcement Learning through Sensorimotor Space EnlargementMatthieu Zimmer, Yann Boniface, Alain DutechJoint IEEE 8th International Conference on Development an… · Laboratoire Lorrain de Recherche en Informatique et ses Applications · Inspire · +3
  36. 2018
    Life-Long Disentangled Representation Learning with Cross-Domain Latent HomologiesAlessandro Achille, Tom Eccles, Löıc Matthey … Irina HigginsNeurIPS
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  37. 2018PDF ↗
  38. 2018PDF ↗
  39. 2018
    A visual auditory model based on Growing Self-Organizing Maps to analyze the taxonomic response in early childhoodValentina Gliozzi, Matteo MadedduCognitive Systems Research · University of Turin
  40. 2018
    Evolving Spiking Neural Networks for online learning over drifting data streamsJesús L. Lobo, Ibai Laña, Javier Del Ser … Nikola KasabovNeural Networks · Euskadiko Parke Teknologikoa · University of the Basque Country · +2
  41. 2018
    Rotate your Networks: Better Weight Consolidation and Less Catastrophic ForgettingXialei Liu, Marc Masana, Luis Herranz … Andrew D. BagdanovICPR · Computer Vision Center · University of Florence
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  42. 2018
    Local learning rules to attenuate forgetting in neural networksMichael Deistler, Martino Sorbaro, Michael E. Rule, Matthias H. HennigarXiv
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  43. 2018
    On catastrophic forgetting and mode collapse in Generative Adversarial NetworksHoang Thanh-Tung, Truyen TranarXiv · Deakin University
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  44. 2018
  45. 2018
    Modeling Consecutive Task Learning with Task Graph AgendasDavid Isele, Eric Eaton, Mark Roberts, David W. AhaAdaptive Agents and Multi-Agents Systems · University of Pennsylvania · United States Naval Research Laboratory
  46. 2018PDF ↗
  47. 2018
    Embodiment can combat catastrophic forgettingJoshua Powers, Sam Kriegman, Josh BongardGenetic and Evolutionary Computation Conference Companion · University of Vermont
  48. 2018
    Policy and Value Transfer in Lifelong Reinforcement LearningDavid Abel, Yuu Jinnai, Yue (Sophie) Guo … M. LittmanICML
  49. 2018
    Combating catastrophic forgetting with developmental compressionShawn L. E. Beaulieu, Sam Kriegman, Josh C. BongardGenetic and Evolutionary Computation Conference · University of Vermont
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  50. 2018
    Enhancing CNN Incremental Learning Capability with an Expanded NetworkShanshan Cai, Zhuwei Xu, Zhichao Huang … C.‐C. Jay KuoIEEE International Conference on Multimedia and Expo (ICME) · University of Southern California · Tsinghua University
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.