| Generative adversarial networks I Goodfellow, J Pouget-Abadie, M Mirza, B Xu, D Warde-Farley, S Ozair, ... Communications of the ACM 63 (11), 139-144, 2020 | 190485* | 2020 |
| Conditional generative adversarial nets M Mirza, S Osindero arXiv preprint arXiv:1411.1784, 2014 | 16881 | 2014 |
| Asynchronous methods for deep reinforcement learning V Mnih, AP Badia, M Mirza, A Graves, T Lillicrap, T Harley, D Silver, ... International conference on machine learning, 1928-1937, 2016 | 14288 | 2016 |
| Maxout networks I Goodfellow, D Warde-Farley, M Mirza, A Courville, Y Bengio International conference on machine learning, 1319-1327, 2013 | 3335 | 2013 |
| Challenges in representation learning: A report on three machine learning contests IJ Goodfellow, D Erhan, PL Carrier, A Courville, M Mirza, B Hamner, ... International conference on neural information processing, 117-124, 2013 | 2702 | 2013 |
| An empirical investigation of catastrophic forgetting in gradient-based neural networks IJ Goodfellow, M Mirza, D Xiao, A Courville, Y Bengio arXiv preprint arXiv:1312.6211, 2013 | 2007 | 2013 |
| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv preprint arXiv:1605.02688, 2016 | 1181 | 2016 |
| Generative adversarial nets G Ian, PA Jean, M Mehdi, X Bing, WF David, O Sherjil, C Aaron, B Yoshua Advances in neural information processing systems 27 (9), 2014 | 778 | 2014 |
| Ozair Sh., Courville A., Bengio Y. Generative Adversarial Networks I Goodfellow, J Pouget-Abadie, M Mirza, B Xu, D Warde-Farley Communications of the ACM 63 (11), 139-144, 2020 | 600* | 2020 |
| Generative adversarial nets J Goodfellow Ian, PA Jean, M Mehdi, X Bing, WF David, O Sherjil, ... Proceedings of the 27th international conference on neural information …, 2014 | 599 | 2014 |
| Generative adversarial networks (2014) IJ Goodfellow, J Pouget-Abadie, M Mirza, B Xu, D Warde-Farley, S Ozair, ... arXiv preprint arXiv:1406.2661 1406, 2019 | 556 | 2019 |
| Emonets: Multimodal deep learning approaches for emotion recognition in video SE Kahou, X Bouthillier, P Lamblin, C Gulcehre, V Michalski, K Konda, ... Journal on Multimodal User Interfaces 10 (2), 99-111, 2016 | 551 | 2016 |
| Combining modality specific deep neural networks for emotion recognition in video SE Kahou, C Pal, X Bouthillier, P Froumenty, Ç Gülçehre, R Memisevic, ... Proceedings of the 15th ACM on International conference on multimodal …, 2013 | 471 | 2013 |
| Pylearn2: a machine learning research library IJ Goodfellow, D Warde-Farley, P Lamblin, V Dumoulin, M Mirza, ... arXiv preprint arXiv:1308.4214, 2013 | 374 | 2013 |
| Disentangling factors of variation for facial expression recognition S Rifai, Y Bengio, A Courville, P Vincent, M Mirza | 279 | 2012 |
| Unsupervised predictive memory in a goal-directed agent G Wayne, CC Hung, D Amos, M Mirza, A Ahuja, A Grabska-Barwinska, ... arXiv preprint arXiv:1803.10760, 2018 | 222 | 2018 |
| Multi-Prediction Deep Boltzmann Machines IJ Goodfellow, M Mirza, A Courville, Y Bengio | 203 | 2013 |
| International conference on machine learning V Mnih, AP Badia, M Mirza, A Graves, T Lillicrap, T Harley, D Silver, ... PMLR, 2016 | 191 | 2016 |
| Generative adversarial nets M Mirza, B Xu, D Warde-Farley, S Ozair, A Courville, Y Bengio, ... Advances in neural information processing systems 27, 2672-2680, 2014 | 167 | 2014 |
| Optimizing agent behavior over long time scales by transporting value CC Hung, T Lillicrap, J Abramson, Y Wu, M Mirza, F Carnevale, A Ahuja, ... Nature communications 10 (1), 5223, 2019 | 159 | 2019 |