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
5630 2016 Universal adversarial perturbations SM Moosavi-Dezfooli, A Fawzi, O Fawzi, P Frossard
Proceedings of the IEEE conference on computer vision and pattern …, 2017
2927 2017 Analysis of classifiers’ robustness to adversarial perturbations A Fawzi, O Fawzi, P Frossard
Machine learning 107 (3), 481-508, 2018
448 * 2018 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
424 2022 Robustness of classifiers: from adversarial to random noise A Fawzi, SM Moosavi-Dezfooli, P Frossard
Advances in neural information processing systems 29, 2016
404 2016 Analysis of classifiers' robustness to adversarial perturbations A Fawzi, O Fawzi, P Frossard
arXiv preprint arXiv:1502.02590, 2015
394 2015 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
338 * 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
323 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
310 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
301 2016 Adversarial vulnerability for any classifier A Fawzi, H Fawzi, O Fawzi
Advances in neural information processing systems 31, 2018
268 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
213 * 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
206 * 2017 Manitest: Are classifiers really invariant? A Fawzi, P Frossard
arXiv preprint arXiv:1507.06535, 2015
134 2015 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
67 2024 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
63 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
61 2015 Robustness of classifiers to uniform JY Franceschi, A Fawzi, O Fawzi
International Conference on Artificial Intelligence and Statistics, 1280-1288, 2018
48 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
44 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
37 2016 