| Bootstrap your own latent-a new approach to self-supervised learning JB Grill, F Strub, F Altché, C Tallec, P Richemond, E Buchatskaya, ... Advances in neural information processing systems 33, 21271-21284, 2020 | 7898 | 2020 |
| 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 | 2437 | 2017 |
| Modulating early visual processing by language H De Vries, F Strub, J Mary, H Larochelle, O Pietquin, AC Courville Advances in neural information processing systems 30, 2017 | 592 | 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 | 474 | 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 | 356* | 2016 |
| 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 | 285 | 2018 |
| Mastering the game of Stratego with model-free multiagent reinforcement learning J Perolat, B De Vylder, D Hennes, E Tarassov, F Strub, V de Boer, ... Science 378 (6623), 990-996, 2022 | 268 | 2022 |
| Collaborative filtering with stacked denoising autoencoders and sparse inputs F Strub, J Mary, P Philippe NIPS workshop on machine learning for eCommerce, 2015 | 239 | 2015 |
| Feature-wise transformations V Dumoulin, E Perez, N Schucher, F Strub, H Vries, A Courville, Y Bengio Distill 3 (7), e11, 2018 | 198* | 2018 |
| 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 | 159* | 2017 |
| Broaden your views for self-supervised video learning A Recasens, P Luc, JB Alayrac, L Wang, F Strub, C Tallec, M Malinowski, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 148 | 2021 |
| 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 | 136 | 2017 |
| 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 | 113 | 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 | 87 | 2020 |
| Emergent communication at scale R Chaabouni, F Strub, F Altché, E Tarassov, C Tallec, E Davoodi, ... International conference on learning representations, 2022 | 86 | 2022 |
| Learning visual reasoning without strong priors E Perez, H De Vries, F Strub, V Dumoulin, A Courville arXiv preprint arXiv:1707.03017, 2017 | 69 | 2017 |
| 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 | 62 | 2016 |
| Harm de Vries, Vincent Dumoulin, and Aaron Courville E Perez, F Strub Film: Visual reasoning with a general conditioning layer 3 (4), 10, 2017 | 57 | 2017 |
| 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 | 56* | 2020 |
| 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 | 50 | 2019 |
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