Antoine Marot — accepted AI-conference papers

2022

LIPS - Learning Industrial Physical Simulation benchmark suite

Milad Leyli-abadi, Antoine Marot, Jérôme Picault, David Danan, Mouadh Yagoubi, Benjamin Donnot +4

NeurIPS 2022accept

Physical simulations are at the core of many critical industrial systems. However, today's physical simulators have some limitations such as computation time, dealing with missing or uncertain data, or even non-convergence for some feasible cases. Recently, the use of data-driven approaches to lea…

Cited by 13 Source ↗PDF ↗Scholar ↗

2020

Deep Statistical Solvers

Balthazar Donon, Zhengying Liu, Wenzhuo LIU, Isabelle Guyon, Antoine Marot, Marc Schoenauer

NeurIPS 2020poster

This paper introduces Deep Statistical Solvers (DSS), a new class of trainable solvers for optimization problems, arising e.g., from system simulations. The key idea is to learn a solver that generalizes to a given distribution of problem instances. This is achieved by directly using as loss the obj…

Cited by 27 Source ↗PDF ↗code ↗Scholar ↗