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Official implementation of "On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning"
An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning
Implementation of "Overcoming catastrophic forgetting in neural networks" in Tensorflow
Code implementation for "Continual Semi-Supervised Learning through Contrastive Interpolation Consistency"
Learning to Prompt (L2P) for Continual Learning @ CVPR22 and DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning @ ECCV22
The main features of google-research/l2p are: Continual Learning Frameworks, Task-Specific Prompting.
Projects with overlapping indexed features include: aimagelab/lider — Official implementation of "On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning". aimagelab/mammoth — An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for… ariseff/overcoming-catastrophic — Implementation of "Overcoming catastrophic forgetting in neural networks" in Tensorflow. arunmallya/packnet — Code for PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning. arunmallya/piggyback — Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights. aimagelab/cssl — Code implementation for "Continual Semi-Supervised Learning through Contrastive Interpolation Consistency".