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Michaël Mathieu
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2020 – today
- 2023
- [i10]Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre
, Shangtong Zhang, Ray Jiang, Tom Le Paine, Richard Powell, Konrad Zolna, Julian Schrittwieser, David H. Choi, Petko Georgiev, Daniel Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aäron van den Oord, Wojciech Marian Czarnecki, Nando de Freitas, Oriol Vinyals:
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR abs/2308.03526 (2023) - 2021
- [i9]Open Ended Learning Team, Adam Stooke, Anuj Mahajan, Catarina Barros, Charlie Deck, Jakob Bauer, Jakub Sygnowski, Maja Trebacz, Max Jaderberg, Michaël Mathieu, Nat McAleese, Nathalie Bradley-Schmieg, Nathaniel Wong, Nicolas Porcel, Roberta Raileanu, Steph Hughes-Fitt, Valentin Dalibard, Wojciech Marian Czarnecki:
Open-Ended Learning Leads to Generally Capable Agents. CoRR abs/2107.12808 (2021)
2010 – 2019
- 2019
- [j1]Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds
Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 575(7782): 350-354 (2019) - 2017
- [b1]Michaël Mathieu:
Unsupervised Learning Under Uncertainty. New York University, USA, 2017 - [c11]Junbo Jake Zhao, Michaël Mathieu, Yann LeCun:
Energy-based Generative Adversarial Networks. ICLR (Poster) 2017 - 2016
- [c10]Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun:
Disentangling factors of variation in deep representation using adversarial training. NIPS 2016: 5041-5049 - [c9]Michaël Mathieu, Camille Couprie, Yann LeCun:
Deep multi-scale video prediction beyond mean square error. ICLR (Poster) 2016 - [i8]Junbo Jake Zhao, Michaël Mathieu, Yann LeCun:
Energy-based Generative Adversarial Network. CoRR abs/1609.03126 (2016) - [i7]Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun:
Disentangling factors of variation in deep representations using adversarial training. CoRR abs/1611.03383 (2016) - 2015
- [c8]Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun:
The Loss Surfaces of Multilayer Networks. AISTATS 2015 - [c7]Ross Goroshin, Michaël Mathieu, Yann LeCun:
Learning to Linearize Under Uncertainty. NIPS 2015: 1234-1242 - [c6]Tomás Mikolov, Armand Joulin, Sumit Chopra, Michaël Mathieu, Marc'Aurelio Ranzato:
Learning Longer Memory in Recurrent Neural Networks. ICLR (Workshop) 2015 - [c5]Nicolas Vasilache, Jeff Johnson, Michaël Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun:
Fast Convolutional Nets With fbfft: A GPU Performance Evaluation. ICLR 2015 - [i6]Junbo Jake Zhao, Michaël Mathieu, Ross Goroshin, Yann LeCun:
Stacked What-Where Auto-encoders. CoRR abs/1506.02351 (2015) - [i5]Ross Goroshin, Michaël Mathieu, Yann LeCun:
Learning to Linearize Under Uncertainty. CoRR abs/1506.03011 (2015) - 2014
- [c4]Michaël Mathieu, Mikael Henaff, Yann LeCun:
Fast Training of Convolutional Networks through FFTs. ICLR (Poster) 2014 - [c3]Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun:
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. ICLR 2014 - [i4]Michaël Mathieu, Yann LeCun:
Fast Approximation of Rotations and Hessians matrices. CoRR abs/1404.7195 (2014) - [i3]Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun:
The Loss Surface of Multilayer Networks. CoRR abs/1412.0233 (2014) - [i2]Marc'Aurelio Ranzato, Arthur Szlam, Joan Bruna, Michaël Mathieu, Ronan Collobert, Sumit Chopra:
Video (language) modeling: a baseline for generative models of natural videos. CoRR abs/1412.6604 (2014) - 2012
- [c2]Guillaume Claret, Michaël Mathieu, David Naccache, Guillaume Seguin:
Physical Simulation of Inarticulate Robots. Cryptography and Security 2012: 491-499 - 2011
- [i1]Guillaume Claret, Michaël Mathieu, David Naccache, Guillaume Seguin:
Physical Simulation of Inarticulate Robots. CoRR abs/1104.1546 (2011) - 2010
- [c1]Koray Kavukcuoglu, Pierre Sermanet, Y-Lan Boureau, Karol Gregor, Michaël Mathieu, Yann LeCun:
Learning Convolutional Feature Hierarchies for Visual Recognition. NIPS 2010: 1090-1098
Coauthor Index
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