tingfengqi

gwfast

A Fisher information matrix python package for GW detector networks.

fisher-information-matrix

PyTorch implementation of FIM and empirical FIM

ewc.pytorch

An implementation of EWC with PyTorch

pytorch-ewc

Unofficial PyTorch implementation of DeepMind's PNAS 2017 paper "Overcoming Catastrophic Forgetting"

Crash-Course-Computer-Science-Chinese

:computer: 计算机速成课 | Crash Course 字幕组 (全40集 2018-5-1 精校完成) B站播放量 383万

BroadLearningSystem

here is the introduce of bls

BroadLearningSystemTools-1.0

Some APIs of Broad Learning System, now BroadLearningSystemTools-2.0 is available.

BroadLearningSystemTools-2.0

New Toolbox of Broad Learning System, with sklearn liked APIs. Created at 2023.08

Incremental-Extreme-Learning-Machines-IELM-

IEML (Incremental Extreme Learning Machines) for the regression and classification problems.

UCL

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

EWC

TensorFlow implementation of Elastic Weight Consolidation

continual-bert

A novel BERT model with online Elastic Weight Loss that learns and consolidates information to mimic memory while minimizing catastrophic forgetting.

EWC

OnlineEWC and EWC++ implementations, the online versions of Elastic weight consolidation

less-forgetful-nns

Demo of Elastic Weight Consolidation to allow a neural network to learn different datasets in sequence.

EWC

TensorFlow v2 + Keras implementation of Elastic Weight Consolidation

Elastic-Weights-Consolidation

Pytorch implementations of Elastic Weight Consolidation (EWC)

Overcoming-Catastrophic-forgetting-in-Neural-Networks

Elastic weight consolidation technique for incremental learning.

TSCIL

[KDD2024] Class-incremental Learning for Time Series: Benchmark and Evaluation

Awesome_Continual-Lifelong-Incremental_learning

CPL

ContinualPTNCN

We introduce Local recurrent Predictive coding model termed as Parallel temporal Neural Coding Network. Unlike classical RNNs, our model is pure local and doesn't require computing gradients backward in time; thus computationally more efficient compared to BPTT and can be used for online learning

continual

Continual Learning of Electronic Health Records (EHR).

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.

variational-continual-learning

Implementation of the variational continual learning method

continual-learning-papers

Continual Learning papers list, curated by ContinualAI

kiwissen-bayesian-trajectory-prediction

Framework for integrating prior knowledge into trajectory prediction models for autonomous driving via Bayesian continual learning.

grad_prediction

[TNNLS 2024] Learning to Predict Gradients for Semi-Supervised Continual Learning

CLTP-MAN

Continual learning-based trajectory prediction with memory augmented networks

continual-learning-mas-cloning-injection-molding

Code to reproduce the results from the paper "Continual Learning of Neural Networks for Quality Prediction in Production using Memory Aware Synapses and Weight Transfer" by Tercan et al., submitted to the Journal of Intelligent Manufacturing

continual-transfer-learning-injection-molding

Code to reproduce the results from the paper "Industrial Transfer Learning: Boosting Machine Learning in Production" by Tercan et al., submitted to the IEEE International Conference on Industrial Informatics, INDIN’19