How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
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"
Implementation for the paper "Adversarial Continual Learning" in PyTorch.
The main features of facebookresearch/adversarial-continual-learning are: Continual Learning Frameworks.
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".