If you need more information about some papers, the code, or if you need the slides, feel free to contact me!

M.A. Charpagne*, F. Strub*, T. M. Pollock
Accurate reconstruction of EBSD datasets by a multimodal data approach using an evolutionary algorithm
International Journal of Science and Engineering Investigations (2019)
Symposium in Algorithm Development in Materials Science and Engineering, TMS (2019) - Oral
Paper: for physician, for machine learner - code

H. van Hasselt, Y. Doron, F. Strub, M. Hessel, N. Sonnerat, J. Modayil
Deep Reinforcement Learning and the Deadly Triad
Deep reinforcement Learning Workshop, NIPS (2018) - Oral
Paper: Paper

F. Strub, M. Seurin, E. Perez, H. de Vries, J. Mary, P. Preux, A. Courville, O. Pietquin
Visual Reasoning with Multi-hop Feature Modulation
In Proc. ECCV (2018)
Paper - code

V. Dumoulin, E. Perez, N. Schucher, F. Strub, H. Vries, A. Courville, Y. Bengio
Feature-wise transformations
In Proc. Distill (2018)

E. Perez, F. Strub, H. Vries, V. Dumoulin, A. Courville
FiLM: Visual Reasoning with a General Conditioning Layer.
In Proc. AAAI - Oral (2018)
Paper - code1 - code2

S. Brodeur, E. Perez, A. Anand, F. Golemo, L. Celotti, F. Strub, J.Rouat, H. Larochelle, A. Courville
HoME: A household multimodal environment.
In Visually-Grounded Interaction and Language Workshop, NIPS 2017
Paper - code - website

E. Perez, H. Vries, F. Strub, V. Dumoulin, A. Courville
Learning Visual Reasoning Without Strong Priors.
In ICML Speech and Language Processing Workshop (2017).
Paper - code1 - code2

H. de Vries* , F. Strub* , J. Mary, H. Larochelle, O. Pietquin, A. Courville
Modulating Early visual Processing by language.
In Proc. of NIPS - Spotlight (2017).
Paper - code

F. Strub, H. de Vries, J. Mary, B. Piot, A. Courville, O. Pietquin
End-to-end optimization of goal-driven and visually grounded dialogue systems.
In Proc. of IJCAI - Oral presentation (2017).
Paper - code - website

H. de Vries, F. Strub, S. Chandar, O. Pietquin, H. Larochelle, A. Courville
GuessWhat?! Visual object discovery through multi-modal dialogue.
In Proc. of CVPR - Spotlight (2017).
Paper - code - website

J. Pérolat, F. Strub, B. Piot, O. Pietquin
Learning Nash Equilibrium for General-Sum Markov Games from Batch Data.
In Proc. of AISTAT (2017).
Paper - code

F. Strub, J. Mary, R. Gaudel
Hybrid Recommender System based on Autoencoders.
In Proc. of Recsys workshop DLRS (2017)
Paper - code

F. Strub, J. Mary, P. Preux
Collaborative Filtering with Stacked Denoising Autoencoders and Sparse Inputs.
In NIPS Workshop on Machine Learning for eCommerce. (2015).
Paper - code

* stands for equal contribution