Alhussein Fawzi
Alhussein Fawzi
Research Scientist, Google DeepMind
Verified email at google.com - Homepage
TitleCited byYear
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
9452016
Universal adversarial perturbations
SM Moosavi-Dezfooli, A Fawzi, O Fawzi, P Frossard
Proceedings of the IEEE conference on computer vision and pattern …, 2017
5112017
Analysis of classifiers’ robustness to adversarial perturbations
A Fawzi, O Fawzi, P Frossard
Machine Learning 107 (3), 481-508, 2018
165*2018
Analysis of classifiers' robustness to adversarial perturbations
A Fawzi, O Fawzi, P Frossard
arXiv preprint arXiv:1502.02590, 2015
1442015
Robustness of classifiers: from adversarial to random noise
A Fawzi, SM Moosavi-Dezfooli, P Frossard
Advances in Neural Information Processing Systems, 1632-1640, 2016
1432016
Adversarial vulnerability for any classifier
A Fawzi, H Fawzi, O Fawzi
Advances in Neural Information Processing Systems, 1178-1187, 2018
552018
The robustness of deep networks: A geometrical perspective
A Fawzi, SM Moosavi-Dezfooli, P Frossard
IEEE Signal Processing Magazine 34 (6), 50-62, 2017
532017
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
442016
Dictionary learning for fast classification based on soft-thresholding
A Fawzi, M Davies, P Frossard
International Journal of Computer Vision 114 (2-3), 306-321, 2015
442015
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
39*2018
Analysis of universal adversarial perturbations
SM Moosavi-Dezfooli, A Fawzi, O Fawzi, P Frossard, S Soatto
arXiv preprint arXiv:1705.09554, 2017
382017
Manitest: Are classifiers really invariant?
A Fawzi, P Frossard
arXiv preprint arXiv:1507.06535, 2015
332015
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
162016
Measuring the effect of nuisance variables on classifiers
A Fawzi, P Frossard
British Machine Vision Conference (BMVC), 2016
122016
Robustness of classifiers to uniform and Gaussian noise
JY Franceschi, A Fawzi, O Fawzi
arXiv preprint arXiv:1802.07971, 2018
102018
Robustness via curvature regularization, and vice versa
SM Moosavi-Dezfooli, A Fawzi, J Uesato, P Frossard
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
92019
Image registration with sparse approximations in parametric dictionaries
A Fawzi, P Frossard
SIAM Journal on Imaging Sciences 6 (4), 2370-2403, 2013
82013
Saas: Speed as a supervisor for semi-supervised learning
S Cicek, A Fawzi, S Soatto
Proceedings of the European Conference on Computer Vision (ECCV), 149-163, 2018
72018
Robustness of classifiers to universal perturbations: A geometric perspective
SM Moosavi-Dezfooli, A Fawzi, O Fawzi, P Frossard, S Soatto
62018
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
5*2019
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