Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
This repository contains the dataset and some code for the paper Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty by Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, and Dawn Song.
We show that self-supervised learning can tremendously improve out-of-distribution detection as well as various types of robustness.
Download the one class ImageNet test set here.
The code requires PyTorch 1.0 + and Python 3+.
Citation
If you find this useful in your research, please consider citing:
@article{hendrycks2019selfsupervised,
title={Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty},
author={Dan Hendrycks and Mantas Mazeika and Saurav Kadavath and Dawn Song},
journal={arXiv preprint arXiv:1906.12340},
year={2019}
}