PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

The implementation code for Uncertainty-based Continual Learning with Adaptive Regularization (Neurips 2019)

[CVPR'22] Official Implementation of "CNLL: A Semi-supervised Approach for Continual Noisy Label Learning"

[ICPR 2022] Official Implementation of the paper "Rethinking Task-Incremental Learning Baselines" accepted in the 26th International Conference on Pattern Recognition.

Implementation of "Ternary Feature Masks: zero-forgetting for task-incremental learning"