Maxime Gazeau

According to our database, Maxime Gazeau authored at least 11 papers between 2014 and 2023.

Collaborative distances:

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

2023

Vision-Language Models as a Source of Rewards.

Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, Hussain Masoom, Kay McKinney, Volodymyr Mnih, Alexander Neitz, Fabio Pardo, Jack Parker-Holder, John Quan, Tim Rocktäschel, Himanshu Sahni, Tom Schaul, Yannick Schroecker, Stephen Spencer, Richie Steigerwald, Luyu Wang, Lei Zhang

CoRR, 2023

A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs.

Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal A. C. Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

In-context Reinforcement Learning with Algorithm Distillation.

Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan A. Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning to Efficiently Propagate for Reasoning on Knowledge Graphs.

Zhaocheng Zhu, Xinyu Yuan, Louis-Pascal A. C. Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang

CoRR, 2022

2021

Higher Order Generalization Error for First Order Discretization of Langevin Diffusion.

Mufan (Bill) Li, Maxime Gazeau

CoRR, 2021

2020

A General System of Differential Equations to Model First-Order Adaptive Algorithms.

André Belotto da Silva, Maxime Gazeau

J. Mach. Learn. Res., 2020

An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise.

Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise.

Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba

CoRR, 2019

2018

Bloch Theory and Spectral Gaps for Linearized Water Waves.

Walter Craig, Maxime Gazeau, Christophe Lacave, Catherine Sulem

SIAM J. Math. Anal., 2018

Scalable Recommender Systems through Recursive Evidence Chains.

Elias Tragas, Calvin Luo, Maxime Gazeau, Kevin Luk, David Duvenaud

CoRR, 2018

2014

Probability and Pathwise Order of Convergence of a Semidiscrete Scheme for the Stochastic Manakov Equation.

Maxime Gazeau

SIAM J. Numer. Anal., 2014