| 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 | 18691 | 2014 |
| Deep learning IJ Goodfellow, Y Bengio, A Courville Nature, 2016 | 16464 | 2016 |
| Representation learning: A review and new perspectives Y Bengio, A Courville, P Vincent IEEE transactions on pattern analysis and machine intelligence 35 (8), 1798-1828, 2013 | 6681 | 2013 |
| Show, attend and tell: Neural image caption generation with visual attention K Xu, J Ba, R Kiros, A Courville, R Salakhutdinov, R Zemel, Y Bengio Proceeding of the International Conference on Machine Learning (arXiv …, 2015 | 4971 | 2015 |
| Improved training of wasserstein gans I Gulrajani, F Ahmed, M Arjovsky, V Dumoulin, AC Courville Advances in neural information processing systems, 5767-5777, 2017 | 2838 | 2017 |
| Why does unsupervised pre-training help deep learning? D Erhan, Y Bengio, A Courville, PA Manzagol, P Vincent, S Bengio Journal of Machine Learning Research 11 (Feb), 625-660, 2010 | 2155 | 2010 |
| Maxout networks IJ Goodfellow, D Warde-Farley, M Mirza, A Courville, Y Bengio arXiv preprint arXiv:1302.4389, 2013 | 1991 | 2013 |
| Brain tumor segmentation with deep neural networks M Havaei, A Davy, D Warde-Farley, A Biard, A Courville, Y Bengio, C Pal, ... Medical image analysis 35, 18-31, 2017 | 1344 | 2017 |
| Building end-to-end dialogue systems using generative hierarchical neural network models IV Serban, A Sordoni, Y Bengio, A Courville, J Pineau Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 1062* | 2016 |
| An empirical evaluation of deep architectures on problems with many factors of variation H Larochelle, D Erhan, A Courville, J Bergstra, Y Bengio Proceedings of the 24th international conference on Machine learning, 473-480, 2007 | 870 | 2007 |
| Adversarially learned inference V Dumoulin, I Belghazi, B Poole, O Mastropietro, A Lamb, M Arjovsky, ... arXiv preprint arXiv:1606.00704, 2016 | 724 | 2016 |
| Describing videos by exploiting temporal structure L Yao, A Torabi, K Cho, N Ballas, C Pal, H Larochelle, A Courville Proceedings of the IEEE international conference on computer vision, 4507-4515, 2015 | 713 | 2015 |
| Visualizing higher-layer features of a deep network D Erhan, Y Bengio, A Courville, P Vincent University of Montreal 1341 (3), 1, 2009 | 689 | 2009 |
| Estimating or propagating gradients through stochastic neurons for conditional computation Y Bengio, N Léonard, A Courville arXiv preprint arXiv:1308.3432, 2013 | 666 | 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 | 614 | 2016 |
| A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues IV Serban, A Sordoni, R Lowe, L Charlin, J Pineau, A Courville, Y Bengio | 512 | 2017 |
| A recurrent latent variable model for sequential data J Chung, K Kastner, L Dinh, K Goel, AC Courville, Y Bengio Advances in neural information processing systems, 2980-2988, 2015 | 500 | 2015 |
| Deep learning of representations: Looking forward Y Bengio International Conference on Statistical Language and Speech Processing, 1-37, 2013 | 494 | 2013 |
| Deep feedforward networks I Goodfellow, Y Bengio, A Courville Deep learning, 168-227, 2016 | 418 | 2016 |
| Bayesian theories of conditioning in a changing world AC Courville, ND Daw, DS Touretzky Trends in cognitive sciences 10 (7), 294-300, 2006 | 409 | 2006 |
Yoshua BengioProfessor, University of Montreal (Computer Sc. & Op. Res.), Mila, CIFAR, CRM, IVADO, REPARTI, GRSNCVerified email at mila.quebec
