Adversarial examples in the physical world A Kurakin, IJ Goodfellow, S Bengio Artificial intelligence safety and security, 99-112, 2018 | 6643 | 2018 |
Fixmatch: Simplifying semi-supervised learning with consistency and confidence K Sohn, D Berthelot, N Carlini, Z Zhang, H Zhang, CA Raffel, ED Cubuk, ... Advances in neural information processing systems 33, 596-608, 2020 | 3673 | 2020 |
Adversarial machine learning at scale A Kurakin, I Goodfellow, S Bengio arXiv preprint arXiv:1611.01236, 2016 | 3627 | 2016 |
Ensemble adversarial training: Attacks and defenses F Tramèr, A Kurakin, N Papernot, I Goodfellow, D Boneh, P McDaniel arXiv preprint arXiv:1705.07204, 2017 | 3266 | 2017 |
Large-scale evolution of image classifiers E Real, S Moore, A Selle, S Saxena, YL Suematsu, J Tan, QV Le, ... International conference on machine learning, 2902-2911, 2017 | 2008 | 2017 |
Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring D Berthelot, N Carlini, ED Cubuk, A Kurakin, K Sohn, H Zhang, C Raffel arXiv preprint arXiv:1911.09785, 2019 | 1210 | 2019 |
On evaluating adversarial robustness N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ... arXiv preprint arXiv:1902.06705, 2019 | 1001 | 2019 |
Adversarial logit pairing H Kannan, A Kurakin, I Goodfellow arXiv preprint arXiv:1803.06373, 2018 | 749 | 2018 |
A real time system for dynamic hand gesture recognition with a depth sensor A Kurakin, Z Zhang, Z Liu 2012 Proceedings of the 20th European signal processing conference (EUSIPCO …, 2012 | 425 | 2012 |
Technical report on the cleverhans v2. 1.0 adversarial examples library N Papernot, F Faghri, N Carlini, I Goodfellow, R Feinman, A Kurakin, ... arXiv preprint arXiv:1610.00768, 2016 | 423 | 2016 |
High accuracy and high fidelity extraction of neural networks M Jagielski, N Carlini, D Berthelot, A Kurakin, N Papernot 29th USENIX security symposium (USENIX Security 20), 1345-1362, 2020 | 396 | 2020 |
Adversarial examples that fool both computer vision and time-limited humans G Elsayed, S Shankar, B Cheung, N Papernot, A Kurakin, I Goodfellow, ... Advances in neural information processing systems 31, 2018 | 376 | 2018 |
Adversarial attacks and defences competition A Kurakin, I Goodfellow, S Bengio, Y Dong, F Liao, M Liang, T Pang, ... The NIPS'17 Competition: Building Intelligent Systems, 195-231, 2018 | 358 | 2018 |
Adamatch: A unified approach to semi-supervised learning and domain adaptation D Berthelot, R Roelofs, K Sohn, N Carlini, A Kurakin arXiv preprint arXiv:2106.04732, 2021 | 152 | 2021 |
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming S Dathathri, K Dvijotham, A Kurakin, A Raghunathan, J Uesato, RR Bunel, ... Advances in Neural Information Processing Systems 33, 5318-5331, 2020 | 114 | 2020 |
How to dp-fy ml: A practical guide to machine learning with differential privacy N Ponomareva, H Hazimeh, A Kurakin, Z Xu, C Denison, HB McMahan, ... Journal of Artificial Intelligence Research 77, 1113-1201, 2023 | 109 | 2023 |
Adversarial examples in the physical world. arXiv 2016 A Kurakin, I Goodfellow, S Bengio arXiv preprint arXiv:1607.02533, 2016 | 104 | 2016 |
Toward training at imagenet scale with differential privacy A Kurakin, S Song, S Chien, R Geambasu, A Terzis, A Thakurta arXiv preprint arXiv:2201.12328, 2022 | 73 | 2022 |
cleverhans v0. 1: an adversarial machine learning library I Goodfellow, N Papernot, PD McDaniel, R Feinman, F Faghri, A Matyasko, ... arXiv preprint arXiv:1610.00768 1, 7, 2016 | 70 | 2016 |
Adversarial vision challenge W Brendel, J Rauber, A Kurakin, N Papernot, B Veliqi, SP Mohanty, ... The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020 | 66 | 2020 |