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Alhussein Fawzi
Alhussein Fawzi
Research Scientist, Google DeepMind
Dirección de correo verificada de google.com - Página principal
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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
62762016
Universal adversarial perturbations
SM Moosavi-Dezfooli, A Fawzi, O Fawzi, P Frossard
Proceedings of the IEEE conference on computer vision and pattern …, 2017
32352017
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
6162022
Analysis of classifiers' robustness to adversarial perturbations
A Fawzi, O Fawzi, P Frossard
arXiv preprint arXiv:1502.02590, 2015
471*2015
Robustness of classifiers: from adversarial to random noise
A Fawzi, SM Moosavi-Dezfooli, P Frossard
Advances in neural information processing systems 29, 2016
4312016
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
385*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
3732019
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
3422019
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
3292016
Adversarial vulnerability for any classifier
A Fawzi, H Fawzi, O Fawzi
Advances in neural information processing systems 31, 2018
2942018
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
2632024
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
236*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
227*2017
Manitest: Are classifiers really invariant?
A Fawzi, P Frossard
arXiv preprint arXiv:1507.06535, 2015
1442015
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
652017
Dictionary learning for fast classification based on soft-thresholding
A Fawzi, M Davies, P Frossard
International Journal of Computer Vision 114, 306-321, 2015
632015
Robustness of classifiers to uniform and Gaussian noise
JY Franceschi, A Fawzi, O Fawzi
International Conference on Artificial Intelligence and Statistics, 1280-1288, 2018
582018
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
542016
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
402016
Verification of deep probabilistic models
K Dvijotham, M Garnelo, A Fawzi, P Kohli
arXiv preprint arXiv:1812.02795, 2018
312018
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Artículos 1–20