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 | 461 | 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 | 235 | 2016 |
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 | 218 | 2017 |
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 | 176* | 2016 |
Collaborative filtering with stacked denoising autoencoders and sparse inputs F Strub, J Mary NIPS workshop on machine learning for eCommerce, 2015 | 129 | 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 | 108* | 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 | 96 | 2020 |
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 | 80 | 2017 |
Feature-wise transformations V Dumoulin, E Perez, N Schucher, F Strub, H Vries, A Courville, Y Bengio Distill 3 (7), e11, 2018 | 68* | 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 | 53 | 2018 |
Learning visual reasoning without strong priors E Perez, H De Vries, F Strub, V Dumoulin, A Courville arXiv preprint arXiv:1707.03017, 2017 | 44 | 2017 |
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 | 16 | 2018 |
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 | 15 | 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 | 12 | 2016 |
Self-educated language agent with hindsight experience replay for instruction following G Cideron, M Seurin, F Strub, O Pietquin arXiv preprint arXiv:1910.09451, 2019 | 8 | 2019 |
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 | 6 | 2020 |
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 | | 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 | | 2020 |
Supervised Seeded Iterated Learning for Interactive Language Learning Y Lu, S Singhal, F Strub, O Pietquin, A Courville arXiv preprint arXiv:2010.02975, 2020 | | 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 | | 2020 |