metadata
license: other
license_name: carso-adapted-rail-m
license_link: LICENSE
datasets:
- cifar10
- cifar100
- jeremyf/tiny-imagent-200
metrics:
- accuracy
pipeline_tag: image-classification
Pre-trained models for the paper "Carefully Blending Adversarial Training and Purification Improves Adversarial Robustness" (Ballarin et al., 2024)
Developed by: Emanuele Ballarin, Alessio Ansuini, Luca Bortolussi
Repository: github.com/emaballarin/CARSO
Paper: "Carefully Blending Adversarial Training and Purification Improves Adversarial Robustness" (Ballarin et al., 2024)
Citation (BibTeX):
@misc{ballarin2023carefully,
title={Carefully Blending Adversarial Training and Purification Improves Adversarial Robustness},
author={Emanuele Ballarin and Alessio Ansuini and Luca Bortolussi},
year={2023},
eprint={2306.06081},
archivePrefix={arXiv},
primaryClass={cs.CV}
}