A Comprehensive Survey of Continual Learning: Theory, Method and
ApplicationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 |
Rehearsal revealed: The limits and merits of revisiting samples in
continual learningIEEE International Conference on Computer Vision (ICCV), 2021 |
Gradient Projection Memory for Continual LearningInternational Conference on Learning Representations (ICLR), 2021 |
Training Networks in Null Space of Feature Covariance for Continual
LearningComputer Vision and Pattern Recognition (CVPR), 2021 |
Continual Learning with Extended Kronecker-factored Approximate
CurvatureComputer Vision and Pattern Recognition (CVPR), 2020 |
Dark Experience for General Continual Learning: a Strong, Simple
BaselineNeural Information Processing Systems (NeurIPS), 2020 |
PyTorch: An Imperative Style, High-Performance Deep Learning LibraryNeural Information Processing Systems (NeurIPS), 2019 |
Orthogonal Gradient Descent for Continual LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 |
Variational Continual LearningInternational Conference on Learning Representations (ICLR), 2017 |
Attention Is All You NeedNeural Information Processing Systems (NeurIPS), 2017 |
Learning without ForgettingIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016 |
Adam: A Method for Stochastic OptimizationInternational Conference on Learning Representations (ICLR), 2014 Diederik P. Kingma Jimmy Ba |