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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.

15 papers of 8,653Sort Recent · Most cited
2006 All papers Clear all
  1. 2006
    Parameter Incremental Learning Algorithm for Neural NetworksSheng Wan, Larry E. BantaIEEE Transactions · West Virginia University
  2. 2006
    Recurrent neural network architecture with pre-synaptic inhibition for incremental learningHiroyuki Ohta, Yukio GunjiNeural Networks · Kobe University
  3. 2006
    Orthogonality is not a panacea: backpropagation and "catastrophic interference".Makoto YamaguchiScandinavian Journal of Psychology · Waseda University
  4. 2006
    Incremental learning of object detectors using a visual shape alphabetAndreas Opelt, Axel Pinz, Andrew ZissermanCVPR · Graz University of Technology · University of Oxford
  5. 2006
    Two Biologically Plausible Network Architectures for the Avoidance of Catastrophic InterferenceJ. Addison, J. MacIntyreArtificial Intelligence and Applications
  6. 2006
    A Neural Model for Context-dependent Sequence LearningLuc Berthouze, Adriaan TijsselingNeural Processing Letters · Food Research Institute · National Institute of Advanced Industrial Science and Technology
  7. 2006
    A new ARTMAP-based neural network for incremental learningMu-Chun Su, Jonathan Lee, Kuo-Lung HsiehNeurocomputing · National Central University
  8. 2006
    A functional hypothesis for adult hippocampal neurogenesis: Avoidance of catastrophic interference in the dentate gyrusLaurenz Wiskott, Malte J. Rasch, Gerd KempermannHippocampus · Humboldt-Universität zu Berlin · Max Planck Society · +3
  9. 2006
    A Class-Incremental Learning Method for Multi-Class Support Vector Machines in Text ClassificationBo-feng Zhang, Jinshu Su, Xin XuICML · National University of Defense Technology
  10. 2006
    Adaptation of Artificial Neural Networks Avoiding Catastrophic ForgettingD. Albesano, Roberto Gemello, Pietro Laface … Stefano ScanzioThe 2006 IEEE International Joint Conference on Neural Ne… · Politecnico di Torino
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  11. 2006
    Alleviating Catastrophic Forgetting via Multi-Objective LearningYaochu Jin, Bernhard SendhoffThe 2006 IEEE International Joint Conference on Neural Ne… · Honda (Japan) · Honda (Germany)
  12. 2006
    A biologically motivated neural network architecture for the avoidance of catastrophic interferenceJ. F. Dale Addison, Garen Arevian, John MacIntyreResearch and Development in Intelligent Systems XXII · University of Sunderland
  13. 2006
    Multi-class Incremental Learning Based on Support Vector MachinesPei YangPreprint
  14. 2006
    Benchmarking Catastrophic Forgetting in Neural NetworksOle-Marius Moe-HelgesenPreprint
  15. 2006
    Reducing catastrophic forgetting in neural networks using slow learningMikael Eikrem VikPreprint
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.