Learning Convolutional Feature Hierarchies for Visual Recognition. - Koray Kavukcuoglu; Pierre Sermanet; Y-Lan Boureau; Karol Gregor; Michaël Mathieu; Yann LeCun (NIPS, 2010)

Physical Simulation of Inarticulate Robots. - Guillaume Claret; Michaël Mathieu; David Naccache; Guillaume Seguin (Cryptography and Security, 2012)

The Loss Surface of Multilayer Networks. - Anna Choromanska; Mikael Henaff; Michaël Mathieu; Gérard Ben Arous; Yann LeCun (CoRR, 2014)

Fast Training of Convolutional Networks through FFTs. - Michaël Mathieu; Mikael Henaff; Yann LeCun (ICLR (Poster), 2014)

Fast Approximation of Rotations and Hessians matrices. - Michaël Mathieu; Yann LeCun (CoRR, 2014)

Video (language) modeling: a baseline for generative models of natural videos. - Marc'Aurelio Ranzato; Arthur Szlam; Joan Bruna; Michaël Mathieu; Ronan Collobert; Sumit Chopra (CoRR, 2014)

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. - Pierre Sermanet; David Eigen; Xiang Zhang 013; Michaël Mathieu; Rob Fergus; Yann LeCun (ICLR, 2014)

The Loss Surfaces of Multilayer Networks. - Anna Choromanska; Mikael Henaff; Michaël Mathieu; Gérard Ben Arous; Yann LeCun (AISTATS, 2015)

Learning to Linearize Under Uncertainty. - Ross Goroshin; Michaël Mathieu; Yann LeCun (NIPS, 2015)

Learning Longer Memory in Recurrent Neural Networks. - Tomás Mikolov; Armand Joulin; Sumit Chopra; Michaël Mathieu; Marc'Aurelio Ranzato (ICLR (Workshop), 2015)

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation. - Nicolas Vasilache; Jeff Johnson; Michaël Mathieu; Soumith Chintala; Serkan Piantino; Yann LeCun (ICLR, 2015)

Stacked What-Where Auto-encoders. - Junbo Jake Zhao; Michaël Mathieu; Ross Goroshin; Yann LeCun (CoRR, 2015)

Disentangling factors of variation in deep representation using adversarial training. - Michaël Mathieu; Junbo Jake Zhao; Pablo Sprechmann; Aditya Ramesh; Yann LeCun (NIPS, 2016)

Deep multi-scale video prediction beyond mean square error. - Michaël Mathieu; Camille Couprie; Yann LeCun (ICLR (Poster), 2016)

Disentangling factors of variation in deep representations using adversarial training. - Michaël Mathieu; Junbo Jake Zhao; Pablo Sprechmann; Aditya Ramesh; Yann LeCun (CoRR, 2016)

Energy-based Generative Adversarial Network. - Junbo Jake Zhao; Michaël Mathieu; Yann LeCun (CoRR, 2016)

Energy-based Generative Adversarial Networks. - Junbo Jake Zhao; Michaël Mathieu; Yann LeCun (ICLR (Poster), 2017)

Unsupervised Learning Under Uncertainty. - Michaël Mathieu (2017)

Grandmaster level in StarCraft II using multi-agent reinforcement learning. - Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; et al. (Nat., 2019)

Open-Ended Learning Leads to Generally Capable Agents. - 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; et al. (CoRR, 2021)

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. - 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; et al. (CoRR, 2023)