Awesome
MART
Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"
Usage
python3 train_resnet.py for ResNet18
python3 train_wideresnet.py for WideResNet
Trained Models
The ResNet18 trained by MART on CIFAR-10: https://drive.google.com/file/d/1YAKnAhUAiv8UFHnZfj2OIHWHpw_HU0Ig/view?usp=sharing
The WideResNet-34-10 trained by MART on CIFAR-10: https://drive.google.com/open?id=1QjEwSskuq7yq86kRKNv6tkn9I16cEBjc
MART WideResNet-28-10 model on 500K unlabeled data: https://drive.google.com/file/d/11pFwGmLfbLHB4EvccFcyHKvGb3fBy_VY/view?usp=sharing
Citing this work
If you use this code in your work, please cite the accompanying paper:
@inproceedings{Wang2020Improving,
title={Improving Adversarial Robustness Requires Revisiting Misclassified Examples},
author={Yisen Wang and Difan Zou and Jinfeng Yi and James Bailey and Xingjun Ma and Quanquan Gu},
booktitle={ICLR},
year={2020}
}
Requirements
- Python 3.7.4
- Pytorch 1.3.1
- Part of the code is based on the following repo: