Avalanche: an End-to-End Library for Continual Learning based on PyTorch.

PyCIL: A Python Toolbox for Class-Incremental Learning

🎉 PILOT: A Pre-trained Model-Based Continual Learning Toolbox

Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.

Evaluate three types of task shifting with popular continual learning algorithms.

A clean and simple data loading library for Continual Learning

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).

A collection of incremental learning paper implementations including PODNet (ECCV20) and Ghost (CVPR-W21).

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

Class-Incremental Learning: A Survey (TPAMI 2024)

TPAMI 2026 | This repository collects awesome survey, resource, and paper for lifelong learning LLM agents

A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

Universal User Representation Pre-training for Cross-domain Recommendation and User Profiling

Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need (IJCV 2024)

Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686

Forward Compatible Few-Shot Class-Incremental Learning (CVPR'22)

Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen, "Compacting, Picking and Growing for Unforgetting Continual Learning," Thirty-third Conference on Neural Information Processing Systems, NeurIPS 2019

PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"

Lifelong Loop Closure Detection (ICRA 2022)