| Film: Visual reasoning with a general conditioning layer E Perez, F Strub, H De Vries, V Dumoulin, A Courville Association for the Advancement of Artificial Intelligence, 2017 | 599 | 2017 |
| Bootstrap your own latent: A new approach to self-supervised learning JB Grill, F Strub, F Altché, C Tallec, PH Richemond, E Buchatskaya, ... arXiv preprint arXiv:2006.07733, 2020 | 410 | 2020 |
| Modulating early visual processing by language H De Vries, F Strub, J Mary, H Larochelle, O Pietquin, A Courville arXiv preprint arXiv:1707.00683, 2017 | 276 | 2017 |
| GuessWhat?! Visual object discovery through multi-modal dialogue H de Vries, F Strub, S Chandar, O Pietquin, H Larochelle, A Courville IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016 | 275 | 2016 |
| Hybrid recommender system based on autoencoders F Strub, R Gaudel, J Mary Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, 11-16, 2016 | 201* | 2016 |
| Collaborative filtering with stacked denoising autoencoders and sparse inputs F Strub, J Mary NIPS workshop on machine learning for eCommerce, 2015 | 145 | 2015 |
| End-to-end optimization of goal-driven and visually grounded dialogue systems F Strub, H De Vries, J Mary, B Piot, A Courville, O Pietquin International Joint Conference on Artificial Intelligence, 2017 | 119* | 2017 |
| HoME: A household multimodal environment S Brodeur, E Perez, A Anand, F Golemo, L Celotti, F Strub, J Rouat, ... Visually-Grounded Interaction and Language Workshop (ViGIL), NIPS, 2017 | 91 | 2017 |
| Feature-wise transformations V Dumoulin, E Perez, N Schucher, F Strub, H Vries, A Courville, Y Bengio Distill 3 (7), e11, 2018 | 86* | 2018 |
| Deep reinforcement learning and the deadly triad H Van Hasselt, Y Doron, F Strub, M Hessel, N Sonnerat, J Modayil Deep Reinforcement Learning Workshop, NIPS, 2018 | 73 | 2018 |
| Learning visual reasoning without strong priors E Perez, H De Vries, F Strub, V Dumoulin, A Courville arXiv preprint arXiv:1707.03017, 2017 | 49 | 2017 |
| Accurate reconstruction of EBSD datasets by a multimodal data approach using an evolutionary algorithm MA Charpagne, F Strub, TM Pollock Materials Characterization 150, 184-198, 2019 | 20 | 2019 |
| Learning Nash Equilibrium for General-Sum Markov Games from Batch Data J Pérolat, F Strub, B Piot, O Pietquin International Conference on Artificial Intelligence and Statistics, 2016 | 18 | 2016 |
| Visual reasoning with multi-hop feature modulation F Strub, M Seurin, E Perez, H De Vries, J Mary, P Preux, ACO Pietquin Proceedings of the European Conference on Computer Vision (ECCV), 784-800, 2018 | 17 | 2018 |
| Higher: Improving instruction following with hindsight generation for experience replay G Cideron, M Seurin, F Strub, O Pietquin 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 225-232, 2020 | 13* | 2020 |
| BYOL works even without batch statistics PH Richemond, JB Grill, F Altché, C Tallec, F Strub, A Brock, S Smith, ... arXiv preprint arXiv:2010.10241, 2020 | 10 | 2020 |
| Countering language drift with seeded iterated learning Y Lu, S Singhal, F Strub, A Courville, O Pietquin International Conference on Machine Learning, 6437-6447, 2020 | 8 | 2020 |
| Broaden Your Views for Self-Supervised Video Learning A Recasens, P Luc, JB Alayrac, L Wang, F Strub, C Tallec, M Malinowski, ... arXiv preprint arXiv:2103.16559, 2021 | 2 | 2021 |
| Supervised seeded iterated learning for interactive language learning Y Lu, S Singhal, F Strub, O Pietquin, A Courville arXiv preprint arXiv:2010.02975, 2020 | 2 | 2020 |
| A Machine of Few Words--Interactive Speaker Recognition with Reinforcement Learning M Seurin, F Strub, P Preux, O Pietquin arXiv preprint arXiv:2008.03127, 2020 | 2 | 2020 |
Aaron CourvilleUniversité de MontréalVerified email at umontreal.ca
