Anish Athalye
Cited by
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Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
A Athalye, N Carlini, D Wagner
International Conference on Machine Learning, 274-283, 2018
Synthesizing Robust Adversarial Examples
A Athalye, L Engstrom, A Ilyas, K Kwok
International Conference on Machine Learning, 284-293, 2017
Black-box Adversarial Attacks with Limited Queries and Information
A Ilyas, L Engstrom, A Athalye, J Lin
International Conference on Machine Learning, 2137-2146, 2018
On evaluating adversarial robustness
N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ...
arXiv preprint arXiv:1902.06705, 2019
On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses
A Athalye, N Carlini
arXiv preprint arXiv:1804.03286, 2018
Pervasive label errors in test sets destabilize machine learning benchmarks
CG Northcutt, A Athalye, J Mueller
arXiv preprint arXiv:2103.14749, 2021
Evaluating and Understanding the Robustness of Adversarial Logit Pairing
L Engstrom, A Ilyas, A Athalye
arXiv preprint arXiv:1807.10272, 2018
pASSWORD tYPOS and How to Correct Them Securely
R Chatterjee, A Athalye, D Akhawe, A Juels, T Ristenpart
IEEE Symposium on Security and Privacy, 2016
Notary: A Device for Secure Transaction Approval
A Athalye, A Belay, MF Kaashoek, R Morris, N Zeldovich
Proceedings of the 27th ACM Symposium on Operating Systems Principles, 97-113, 2019
rtlv: push-button verification of software on hardware
N Moroze, A Athalye, MF Kaashoek, N Zeldovich
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