| Deepfool: a simple and accurate method to fool deep neural networks SM Moosavi-Dezfooli, A Fawzi, P Frossard Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 6110 | 2016 |
| Universal adversarial perturbations SM Moosavi-Dezfooli, A Fawzi, O Fawzi, P Frossard Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 3145 | 2017 |
| Discovering faster matrix multiplication algorithms with reinforcement learning A Fawzi, M Balog, A Huang, T Hubert, B Romera-Paredes, M Barekatain, ... Nature 610 (7930), 47-53, 2022 | 561 | 2022 |
| Analysis of classifiers' robustness to adversarial perturbations A Fawzi, O Fawzi, P Frossard arXiv preprint arXiv:1502.02590, 2015 | 467* | 2015 |
| Robustness of classifiers: from adversarial to random noise A Fawzi, SM Moosavi-Dezfooli, P Frossard Advances in neural information processing systems 29, 2016 | 424 | 2016 |
| Are Labels Required for Improving Adversarial Robustness? J Uesato, JB Alayrac, PS Huang, R Stanforth, A Fawzi, P Kohli arXiv preprint arXiv:1905.13725, 2019 | 365* | 2019 |
| Robustness via curvature regularization, and vice versa SM Moosavi-Dezfooli, A Fawzi, J Uesato, P Frossard Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 358 | 2019 |
| Adversarial robustness through local linearization C Qin, J Martens, S Gowal, D Krishnan, K Dvijotham, A Fawzi, S De, ... Advances in neural information processing systems 32, 2019 | 335 | 2019 |
| Adaptive data augmentation for image classification A Fawzi, H Samulowitz, D Turaga, P Frossard 2016 IEEE international conference on image processing (ICIP), 3688-3692, 2016 | 325 | 2016 |
| Adversarial vulnerability for any classifier A Fawzi, H Fawzi, O Fawzi Advances in neural information processing systems 31, 2018 | 284 | 2018 |
| Empirical study of the topology and geometry of deep networks A Fawzi, SM Moosavi-Dezfooli, P Frossard, S Soatto Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 232* | 2018 |
| The robustness of deep networks: A geometrical perspective A Fawzi, SM Moosavi-Dezfooli, P Frossard IEEE Signal Processing Magazine 34 (6), 50-62, 2017 | 219* | 2017 |
| Mathematical discoveries from program search with large language models B Romera-Paredes, M Barekatain, A Novikov, M Balog, MP Kumar, ... Nature 625 (7995), 468-475, 2024 | 197 | 2024 |
| Manitest: Are classifiers really invariant? A Fawzi, P Frossard arXiv preprint arXiv:1507.06535, 2015 | 144 | 2015 |
| Robustness of classifiers to universal perturbations: A geometric perspective SM Moosavi-Dezfooli, A Fawzi, O Fawzi, P Frossard, S Soatto arXiv preprint arXiv:1705.09554, 2017 | 64 | 2017 |
| Dictionary learning for fast classification based on soft-thresholding A Fawzi, M Davies, P Frossard International Journal of Computer Vision 114, 306-321, 2015 | 62 | 2015 |
| Robustness of classifiers to uniform and Gaussian noise JY Franceschi, A Fawzi, O Fawzi International Conference on Artificial Intelligence and Statistics, 1280-1288, 2018 | 55 | 2018 |
| Measuring the effect of nuisance variables on classifiers A Fawzi, P Frossard Proceedings of the British Machine Vision Conference (BMVC), 137.1-137.12, 2016 | 53 | 2016 |
| Image inpainting through neural networks hallucinations A Fawzi, H Samulowitz, D Turaga, P Frossard 2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop …, 2016 | 39 | 2016 |
| Verification of deep probabilistic models K Dvijotham, M Garnelo, A Fawzi, P Kohli arXiv preprint arXiv:1812.02795, 2018 | 31 | 2018 |
