Mikael Henaff

According to our database, Mikael Henaff authored at least 25 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MaestroMotif: Skill Design from Artificial Intelligence Feedback.

Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro

CoRR, 2024

Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback.

Qinqing Zheng, Mikael Henaff, Amy Zhang, Aditya Grover, Brandon Amos

CoRR, 2024

Generalization to New Sequential Decision Making Tasks with In-Context Learning.

Sharath Chandra Raparthy, Eric Hambro, Robert Kirk, Mikael Henaff, Roberta Raileanu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Motif: Intrinsic Motivation from Artificial Intelligence Feedback.

Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff

Proceedings of the Twelfth International Conference on Learning Representations, 2024

OpenEQA: Embodied Question Answering in the Era of Foundation Models.

Arjun Majumdar, Anurag Ajay, Xiaohan Zhang, Pranav Putta, Sriram Yenamandra, Mikael Henaff, Sneha Silwal, Paul McVay, Oleksandr Maksymets, Sergio Arnaud, Karmesh Yadav, Qiyang Li, Ben Newman, Mohit Sharma, Vincent-Pierre Berges, Shiqi Zhang, Pulkit Agrawal, Yonatan Bisk, Dhruv Batra, Mrinal Kalakrishnan, Franziska Meier, Chris Paxton, Alexander Sax, Aravind Rajeswaran

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories.

Qinqing Zheng, Mikael Henaff, Brandon Amos, Aditya Grover

Proceedings of the International Conference on Machine Learning, 2023

A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs.

Mikael Henaff, Minqi Jiang, Roberta Raileanu

Proceedings of the International Conference on Machine Learning, 2023

2022

Exploration via Elliptical Episodic Bonuses.

Mikael Henaff, Roberta Raileanu, Minqi Jiang, Tim Rocktäschel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning.

Alekh Agarwal, Mikael Henaff, Sham M. Kakade, Wen Sun

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning.

Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford

Proceedings of the 37th International Conference on Machine Learning, 2020

Disagreement-Regularized Imitation Learning.

Kianté Brantley, Wen Sun, Mikael Henaff

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Explicit Explore-Exploit Algorithms in Continuous State Spaces.

Mikael Henaff

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic.

Mikael Henaff, Alfredo Canziani, Yann LeCun

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Deep Networks for Forward Prediction and Planning.

Mikael Henaff

PhD thesis, 2018

2017

Prediction Under Uncertainty with Error-Encoding Networks.

Mikael Henaff, Junbo Jake Zhao, Yann LeCun

CoRR, 2017

Model-Based Planning in Discrete Action Spaces.

Mikael Henaff, William F. Whitney, Yann LeCun

CoRR, 2017

Tracking the World State with Recurrent Entity Networks.

Mikael Henaff, Jason Weston, Arthur Szlam, Antoine Bordes, Yann LeCun

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Orthogonal RNNs and Long-Memory Tasks.

Mikael Henaff, Arthur Szlam, Yann LeCun

CoRR, 2016

Recurrent Orthogonal Networks and Long-Memory Tasks.

Mikael Henaff, Arthur Szlam, Yann LeCun

Proceedings of the 33nd International Conference on Machine Learning, 2016

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

Deep Convolutional Networks on Graph-Structured Data.

Mikael Henaff, Joan Bruna, Yann LeCun

CoRR, 2015

The Loss Surfaces of Multilayer Networks.

Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Fast Training of Convolutional Networks through FFTs.

Michaël Mathieu, Mikael Henaff, Yann LeCun

Proceedings of the 2nd International Conference on Learning Representations, 2014

The Loss Surface of Multilayer Networks.

Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun

CoRR, 2014

2011

Unsupervised Learning of Sparse Features for Scalable Audio Classification.

Mikael Henaff, Kevin Jarrett, Koray Kavukcuoglu, Yann LeCun

Proceedings of the 12th International Society for Music Information Retrieval Conference, 2011