Florian STRUB
Florian STRUB
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Cited by
Cited by
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
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
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, 6594-6604, 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
Collaborative filtering with stacked denoising autoencoders and sparse inputs
F Strub, J Mary
NIPS workshop on machine learning for eCommerce, 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
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
Feature-wise transformations
V Dumoulin, E Perez, N Schucher, F Strub, H Vries, A Courville, Y Bengio
Distill 3 (7), e11, 2018
Learning visual reasoning without strong priors
E Perez, H De Vries, F Strub, V Dumoulin, A Courville
arXiv preprint arXiv:1707.03017, 2017
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
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
Visual reasoning with multi-hop feature modulation
F Strub, M Seurin, E Perez, H De Vries, J Mary, P Preux, ...
Proceedings of the European Conference on Computer Vision (ECCV), 784-800, 2018
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
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
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
Countering language drift with seeded iterated learning
Y Lu, S Singhal, F Strub, O Pietquin, A Courville
arXiv preprint arXiv:2003.12694, 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
The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction
A Martin, C Ollion, F Strub, SL Corff, O Pietquin
arXiv preprint arXiv:2007.08620, 2020
Visually grounded interaction and language
F Strub, H de Vries, A Das, S Kottur, S Lee, M Malinowski, O Pietquin, ...
Schedule Highlights - NIPS Workshop, 2017
A Machine of Few Words--Interactive Speaker Recognition with Reinforcement Learning Download PDF
M Seurin, F Strub, P Preux, O Pietquin
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