Thomas Mesnard

According to our database, Thomas Mesnard authored at least 18 papers between 2015 and 2024.

Collaborative distances:

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

2024

Gemma: Open Models Based on Gemini Research and Technology.

Thomas Mesnard, Cassidy Hardin, Robert Dadashi, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Léonard Hussenot, Aakanksha Chowdhery, Adam Roberts, Aditya Barua, Alex Botev, Alex Castro-Ros, Ambrose Slone, Amélie Héliou, Andrea Tacchetti, Anna Bulanova, Antonia Paterson, Beth Tsai, Bobak Shahriari, Charline Le Lan, Christopher A. Choquette-Choo, Clément Crepy, Daniel Cer, Daphne Ippolito, David Reid, Elena Buchatskaya, Eric Ni, Eric Noland, Geng Yan, George Tucker, George-Christian Muraru, Grigory Rozhdestvenskiy, Henryk Michalewski, Ian Tenney, Ivan Grishchenko, Jacob Austin, James Keeling, Jane Labanowski, Jean-Baptiste Lespiau, Jeff Stanway, Jenny Brennan, Jeremy Chen, Johan Ferret, Justin Chiu, et al.

CoRR, 2024

Direct Language Model Alignment from Online AI Feedback.

Shangmin Guo, Biao Zhang, Tianlin Liu, Tianqi Liu, Misha Khalman, Felipe Llinares, Alexandre Ramé, Thomas Mesnard, Yao Zhao, Bilal Piot, Johan Ferret, Mathieu Blondel

CoRR, 2024

2023

A Survey of Temporal Credit Assignment in Deep Reinforcement Learning.

Eduardo Pignatelli, Johan Ferret, Matthieu Geist, Thomas Mesnard, Hado van Hasselt, Laura Toni

CoRR, 2023

Nash Learning from Human Feedback.

Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Zhaohan Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot

CoRR, 2023

RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback.

Harrison Lee, Samrat Phatale, Hassan Mansoor, Kellie Lu, Thomas Mesnard, Colton Bishop, Victor Carbune, Abhinav Rastogi

CoRR, 2023

Quantile Credit Assignment.

Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Rémi Munos

Proceedings of the International Conference on Machine Learning, 2023

Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments.

Daniel Jarrett, Corentin Tallec, Florent Altché, Thomas Mesnard, Rémi Munos, Michal Valko

Proceedings of the International Conference on Machine Learning, 2023

2022

Curiosity in hindsight.

Daniel Jarrett, Corentin Tallec, Florent Altché, Thomas Mesnard, Rémi Munos, Michal Valko

CoRR, 2022

2021

Geometric Entropic Exploration.

Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Alaa Saade, Shantanu Thakoor, Bilal Piot, Bernardo Ávila Pires, Michal Valko, Thomas Mesnard, Tor Lattimore, Rémi Munos

CoRR, 2021

Counterfactual Credit Assignment in Model-Free Reinforcement Learning.

Thomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S. Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Rémi Munos

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Counterfactual Credit Assignment in Model-Free Reinforcement Learning.

Thomas Mesnard, Théophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Tom Stepleton, Nicolas Heess, Arthur Guez, Marcus Hutter, Lars Buesing, Rémi Munos

CoRR, 2020

2019

Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks.

Thomas Mesnard, Gaëtan Vignoud, João Sacramento, Walter Senn, Yoshua Bengio

CoRR, 2019

Hindsight Credit Assignment.

Anna Harutyunyan, Will Dabney, Thomas Mesnard, Mohammad Gheshlaghi Azar, Bilal Piot, Nicolas Heess, Hado van Hasselt, Gregory Wayne, Satinder Singh, Doina Precup, Rémi Munos

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

2018

Generalization of Equilibrium Propagation to Vector Field Dynamics.

Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio

CoRR, 2018

Extending the Framework of Equilibrium Propagation to General Dynamics.

Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

STDP-Compatible Approximation of Backpropagation in an Energy-Based Model.

Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhuai Wu

Neural Comput., 2017

2016

Towards deep learning with spiking neurons in energy based models with contrastive Hebbian plasticity.

Thomas Mesnard, Wulfram Gerstner, Johanni Brea

CoRR, 2016

2015

An objective function for STDP.

Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhai Wu

CoRR, 2015