Unsupervised Learning of Sparse Features for Scalable Audio Classification. - Mikael Henaff; Kevin Jarrett; Koray Kavukcuoglu; Yann LeCun (ISMIR, 2011)

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)

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

Deep Convolutional Networks on Graph-Structured Data. - Mikael Henaff; Joan Bruna; Yann LeCun (CoRR, 2015)

Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery. - Alexander R. Statnikov; Sisi Ma; Mikael Henaff; Nikita I. Lytkin; Efstratios Efstathiadis; Eric R. Peskin; Constantin F. Aliferis (J. Mach. Learn. Res., 2015)

Recurrent Orthogonal Networks and Long-Memory Tasks. - Mikael Henaff; Arthur Szlam; Yann LeCun (ICML, 2016)

Orthogonal RNNs and Long-Memory Tasks. - Mikael Henaff; Arthur Szlam; Yann LeCun (CoRR, 2016)

Tracking the World State with Recurrent Entity Networks. - Mikael Henaff; Jason Weston; Arthur Szlam; Antoine Bordes; Yann LeCun (ICLR (Poster), 2017)

Model-Based Planning in Discrete Action Spaces. - Mikael Henaff; William F. Whitney; Yann LeCun (CoRR, 2017)

Prediction Under Uncertainty with Error-Encoding Networks. - Mikael Henaff; Junbo Jake Zhao; Yann LeCun (CoRR, 2017)

Deep Networks for Forward Prediction and Planning. - Mikael Henaff (2018)

Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic. - Mikael Henaff; Alfredo Canziani; Yann LeCun (ICLR (Poster), 2019)

Explicit Explore-Exploit Algorithms in Continuous State Spaces. - Mikael Henaff (NeurIPS, 2019)

Disagreement-Regularized Imitation Learning. - Kianté Brantley; Wen Sun 002; Mikael Henaff (ICLR, 2020)

Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning. - Dipendra Misra; Mikael Henaff; Akshay Krishnamurthy; John Langford 001 (ICML, 2020)

PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning. - Alekh Agarwal; Mikael Henaff; Sham M. Kakade; Wen Sun 002 (NeurIPS, 2020)

Exploration via Elliptical Episodic Bonuses. - Mikael Henaff; Roberta Raileanu; Minqi Jiang; Tim Rocktäschel (NeurIPS, 2022)

A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs. - Mikael Henaff; Minqi Jiang; Roberta Raileanu (ICML, 2023)

Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories. - Qinqing Zheng; Mikael Henaff; Brandon Amos; Aditya Grover (ICML, 2023)

OpenEQA: Embodied Question Answering in the Era of Foundation Models. - Arjun Majumdar; Anurag Ajay; Xiaohan Zhang 002; Pranav Putta; Sriram Yenamandra; Mikael Henaff; Sneha Silwal; Paul McVay; Oleksandr Maksymets; Sergio Arnaud; Karmesh Yadav; Qiyang Li; et al. (CVPR, 2024)

Motif: Intrinsic Motivation from Artificial Intelligence Feedback. - Martin Klissarov; Pierluca D'Oro; Shagun Sodhani; Roberta Raileanu; Pierre-Luc Bacon; Pascal Vincent; Amy Zhang 001; Mikael Henaff (ICLR, 2024)

Generalization to New Sequential Decision Making Tasks with In-Context Learning. - Sharath Chandra Raparthy; Eric Hambro; Robert Kirk; Mikael Henaff; Roberta Raileanu (ICML, 2024)

Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback. - Qinqing Zheng; Mikael Henaff; Amy Zhang 001; Aditya Grover; Brandon Amos (CoRR, 2024)

Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass. - Jianing Yang; Alexander Sax; Kevin J. Liang; Mikael Henaff; Hao Tang; Ang Cao; Joyce Chai; Franziska Meier; Matt Feiszli (CVPR, 2025)

MaestroMotif: Skill Design from Artificial Intelligence Feedback. - Martin Klissarov; Mikael Henaff; Roberta Raileanu; Shagun Sodhani; Pascal Vincent; Amy Zhang 001; Pierre-Luc Bacon; Doina Precup; Marlos C. Machado; Pierluca D'Oro (ICLR, 2025)

Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D. - Sergio Arnaud; Paul McVay; Ada Martin; Arjun Majumdar; Krishna Murthy Jatavallabhula; Phillip Thomas; Ruslan Partsey; Daniel Dugas; Abha Gejji; Alexander Sax; Vincent-Pierre Berges; Mikael Henaff; et al. (CoRR, 2025)