Continual Learning With Filter Atom Swapping
Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR’22 Spolight) Paper
If find the repo helpful for your work, please cite the following bib entries:
@inproceedings{Miao_2022_CLatoms,
title={Continual Learning With Filter Atom Swapping},
author={Miao, Zichen and Wang, Ze and Chen, Wei and Qiu, Qiang},
booktitle={International Conference on Learning Representations},
year={2022}}
Requirements
Class-incremental experiments
Dataset
CIFAR100 will be automatically downloaded to ‘Datasets’ dir. Please download ImageNet to ‘Datasets/ImageNet’
Training Scripts
cifar100 (N=5)
$ ./train_dcf_c100.sh 6 GPU_TO_USE
cifar100 (N=10)
$ ./train_dcf_c100.sh 11 GPU_TO_USE
ImageNet-Sub (N=5)
$ ./train_dcf_img100.sh 6 GPU_TO_USE
ImageNet-Sub (N=10)
$ ./train_dcf_img100.sh 11 GPU_TO_USE
Results
