”continual-learning“ 的搜索结果

#计算机科学#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.

Relevant papers in Continual Learning

#计算机科学#Evaluate three types of task shifting with popular continual learning algorithms.

#Awesome#Continual Learning papers list, curated by ContinualAI

#计算机科学#A collection of online continual learning paper implementations and tricks for computer vision in PyTorch, including our ASER(AAAI-21), SCR(CVPR21-W) and survey (Neurocomputing).

Continual learning baselines and strategies from popular papers, using Avalanche. We include EWC, SI, GEM, AGEM, LwF, iCarl, GDumb, and other strategies.

A list of papers, blogs, datasets and software in the field of lifelong/continual machine learning

Implementation of the variational continual learning method

#计算机科学#An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning

Implementation for the paper "Adversarial Continual Learning" in PyTorch.

Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping through Continual Learning. http://continual-slam.cs.uni-freiburg.de

#计算机科学#Learning to Prompt (L2P) for Continual Learning @ CVPR22 and DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning @ ECCV22

An Incremental Learning, Continual Learning, and Life-Long Learning Repository

#计算机科学#Library for automatic retraining and continual learning

Progressive Prompts: Continual Learning for Language Models

Code for the NeurIPS19 paper "Meta-Learning Representations for Continual Learning"

#计算机科学#PyTorch Implementation of Learning to Prompt (L2P) for Continual Learning @ CVPR22

#计算机科学#Continual Learning tutorials and demo running on Google Colaboratory.

#自然语言处理#PyContinual (An Easy and Extendible Framework for Continual Learning)

#计算机科学#🎉 PILOT: A Pre-trained Model-Based Continual Learning Toolbox

#计算机科学#A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.

A clean and simple data loading library for Continual Learning

#计算机科学#CORe50: a new Dataset and Benchmark for Continual Learning

Continual Learning with Echo State Networks experiments