@techreport{dl-16-1,
  title = {{Explaining and Harnessing Adversarial Examples}},
  author = {Goodfellow, Ian J. and Shlens, Jonathon and Szegedy, Christian},
  institution = {arXiv:1412.6572},
  year = {2014},
  url = {https://arxiv.org/abs/1412.6572}
}

@inproceedings{dl-16-2,
  title = {{Towards Deep Learning Models Resistant to Adversarial Attacks}},
  author = {Madry, Aleksander and Makelov, Aleksandar and Schmidt, Ludwig and Tsipras, Dimitris and Vladu, Adrian},
  booktitle = {International Conference on Learning Representations},
  year = {2018},
  url = {https://openreview.net/pdf?id=rJzIBfZAb}
}

@inproceedings{dl-16-3,
  title = {{Certified Adversarial Robustness via Randomized Smoothing}},
  author = {Cohen, Jeremy and Rosenfeld, Elan and Kolter, J. Zico},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning},
  year = {2019},
  url = {https://proceedings.mlr.press/v97/cohen19c.html}
}