3 citations · 3 across the 5 of their papers we have counts for
5 papers
High Throughput Training of Deep Surrogates from Large Ensemble Runs
Lucas Meyer, Marc Schouler, Robert Alexander Caulk +2
Recent years have seen a surge in deep learning approaches to accelerate numerical solvers, which provide faithful but computationally intensive simulations of the physical world.…
Training Deep Surrogate Models with Large Scale Online Learning
Lucas Meyer, Marc Schouler, Robert Alexander Caulk +2
The spatiotemporal resolution of Partial Differential Equations (PDEs) plays important roles in the mathematical description of the world's physical phenomena. In general, scientis…
Simulation-Based Parallel Training
Lucas Meyer, Alejandro Ribés, Bruno Raffin
Numerical simulations are ubiquitous in science and engineering. Machine learning for science investigates how artificial neural architectures can learn from these simulations to s…
Square coloring planar graphs with automatic discharging
Nicolas Bousquet, Lucas de Meyer, Quentin Deschamps +1
The discharging method is a powerful proof technique, especially for graph coloring problems. Its major downside is that it often requires lengthy case analyses, which are sometime…
Deep Surrogate for Direct Time Fluid Dynamics
Lucas Meyer, Louen Pottier, Alejandro Ribes +1
The ubiquity of fluids in the physical world explains the need to accurately simulate their dynamics for many scientific and engineering applications. Traditionally, well establish…