| Generative adversarial nets I Goodfellow, J Pouget-Abadie, M Mirza, B Xu, D Warde-Farley, S Ozair, ... Advances in neural information processing systems, 2672-2680, 2014 | 22894 | 2014 |
| Deep learning I Goodfellow, Y Bengio, A Courville, Y Bengio MIT press, 2016 | 20914 | 2016 |
| Tensorflow: A system for large-scale machine learning M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ... 12th {USENIX} symposium on operating systems design and implementation …, 2016 | 15143* | 2016 |
| TensorFlow: Large-scale machine learning on heterogeneous systems M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... | 7125 | 2015 |
| Explaining and Harnessing Adversarial Examples I Goodfellow, J Shlens, C Szegedy ICLR, 2014 | 5485 | 2014 |
| Intriguing properties of neural networks C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ... arXiv preprint arXiv:1312.6199, 2013 | 5276 | 2013 |
| Improved techniques for training gans T Salimans, I Goodfellow, W Zaremba, V Cheung, A Radford, X Chen Advances in neural information processing systems, 2234-2242, 2016 | 3930 | 2016 |
| Maxout networks I Goodfellow, D Warde-Farley, M Mirza, A Courville, Y Bengio International conference on machine learning, 1319-1327, 2013 | 2132 | 2013 |
| Adversarial examples in the physical world A Kurakin, I Goodfellow, S Bengio arXiv preprint arXiv:1607.02533, 2016 | 1915 | 2016 |
| Theano: new features and speed improvements F Bastien, P Lamblin, R Pascanu, J Bergstra, I Goodfellow, A Bergeron, ... arXiv preprint arXiv:1211.5590, 2012 | 1484 | 2012 |
| Adversarial autoencoders A Makhzani, J Shlens, N Jaitly, I Goodfellow, B Frey arXiv preprint arXiv:1511.05644, 2015 | 1389 | 2015 |
| Practical black-box attacks against machine learning N Papernot, P McDaniel, I Goodfellow, S Jha, ZB Celik, A Swami Proceedings of the 2017 ACM on Asia conference on computer and …, 2017 | 1370 | 2017 |
| Deep learning with differential privacy M Abadi, A Chu, I Goodfellow, HB McMahan, I Mironov, K Talwar, L Zhang Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications …, 2016 | 1286 | 2016 |
| Adversarial machine learning at scale A Kurakin, I Goodfellow, S Bengio arXiv preprint arXiv:1611.01236, 2016 | 1058 | 2016 |
| Self-attention generative adversarial networks H Zhang, I Goodfellow, D Metaxas, A Odena International Conference on Machine Learning, 7354-7363, 2019 | 1022 | 2019 |
| NIPS 2016 tutorial: Generative adversarial networks I Goodfellow arXiv preprint arXiv:1701.00160, 2016 | 1009 | 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 | 952 | 2017 |
| Transferability in machine learning: from phenomena to black-box attacks using adversarial samples N Papernot, P McDaniel, I Goodfellow arXiv preprint arXiv:1605.07277, 2016 | 721 | 2016 |
| Unsupervised learning for physical interaction through video prediction C Finn, I Goodfellow, S Levine Advances in neural information processing systems, 64-72, 2016 | 618 | 2016 |
| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv, arXiv: 1605.02688, 2016 | 595 | 2016 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARAdresse e-mail validée de umontreal.ca
