elastic-weight-consolidation
There are 15 repositories under elastic-weight-consolidation topic.
GMvandeVen/continual-learning
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.
ContinualAI/continual-learning-baselines
Continual learning baselines and strategies from popular papers, using Avalanche. We include EWC, SI, GEM, AGEM, LwF, iCarl, GDumb, and other strategies.
GMvandeVen/brain-inspired-replay
A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).
Mattdl/CLsurvey
Continual Hyperparameter Selection Framework. Compares 11 state-of-the-art Lifelong Learning methods and 4 baselines. Official Codebase of "A continual learning survey: Defying forgetting in classification tasks." in IEEE TPAMI.
shivamsaboo17/Overcoming-Catastrophic-forgetting-in-Neural-Networks
Elastic weight consolidation technique for incremental learning.
GMvandeVen/class-incremental-learning
PyTorch implementation of a VAE-based generative classifier, as well as other class-incremental learning methods that do not store data (DGR, BI-R, EWC, SI, CWR, CWR+, AR1, the "labels trick", SLDA).
mabirck/CatastrophicForgetting-EWC
#WORK IN PROGRESS PyTorch Implementation of Supervised and Deep Q-Learning EWC(Elastic Weight Consolidation), introduced in "Overcoming Catastrophic Forgetting in Neural Networks"
fwiech/incremental-machine-learning
comparative evaluation of incremental machine learning methods
TimoFlesch/elastic-weight-consolidation
Tensorflow 1.x implementation of EWC, evaluated on permuted MNIST
TheUnsolvedDev/Sentiment-Analysis-With-Multi-Domain-Adaptation
Multi domain adaption of quick sentiment analysis on mutliple catagories of task like classification of the nature of the reviews regrading various objects found in Amazon website
hmcalister/Neural-Network-Weight-Importance-Measures
An investigation into weight importance measures in neural networks, relating to sequential learning and interpretability.
hmcalister/Tensorflow-Intepretability-Project
An investigation into sequential learning of tasks using feed-forward networks built with Tensorflow
sabaaslam6038/CEL
CEL Continual Learning
zxllxz2/continual_learning
This is the temporary version of the MINT Lab continual-learning website.
antodima/master-thesis
Federated Echo State Networks for Stress Prediction in the Automotive Use Case. Master Thesis in Artificial Intelligence @ University of Pisa