| Adversarial examples in the physical world A Kurakin, IJ Goodfellow, S Bengio Artificial intelligence safety and security, 99-112, 2018 | 3827 | 2018 |
| Adversarial machine learning at scale A Kurakin, I Goodfellow, S Bengio arXiv preprint arXiv:1611.01236, 2016 | 2200 | 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 | 1969 | 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 | 1319 | 2017 |
| 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 | 933 | 2020 |
| On evaluating adversarial robustness N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ... arXiv preprint arXiv:1902.06705, 2019 | 544 | 2019 |
| Adversarial logit pairing H Kannan, A Kurakin, I Goodfellow arXiv preprint arXiv:1803.06373, 2018 | 467 | 2018 |
| 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 | 446 | 2019 |
| 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 | 371 | 2012 |
| 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 | 255 | 2018 |
| 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 | 242 | 2016 |
| 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 | 217 | 2018 |
| 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 | 136 | 2020 |
| Dynamic hand gesture recognition using depth data Z Zhang, AV Kurakin US Patent 9,536,135, 2017 | 51 | 2017 |
| cleverhans v0. 1: an adversarial machine learning library I Goodfellow, N Papernot, P McDaniel, R Feinman, F Faghri, A Matyasko, ... arXiv preprint arXiv:1610.00768 1, 2016 | 44 | 2016 |
| 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 | 41 | 2020 |
| Adversarial examples in the physical world. arXiv 2016 A Kurakin, I Goodfellow, S Bengio arXiv preprint arXiv:1607.02533, 2016 | 38 | 2016 |
| Adversarial vision challenge W Brendel, J Rauber, A Kurakin, N Papernot, B Veliqi, M Salathé, ... arXiv preprint arXiv:1808.01976, 2018 | 31 | 2018 |
| High-fidelity extraction of neural network models M Jagielski, N Carlini, D Berthelot, A Kurakin, N Papernot arXiv preprint arXiv:1909.01838, 2019 | 30 | 2019 |
| Adversarial machine learning at scale. arXiv 2016 A Kurakin, I Goodfellow, S Bengio arXiv preprint arXiv:1611.01236, 0 | 23 | |
Ian GoodfellowVerified email at cs.stanford.edu
