3 papers
cs.LG2025
NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis
Mouadh Yagoubi, David Danan, Milad Leyli-Abadi +15
The integration of machine learning (ML) into the physical sciences is reshaping computational paradigms, offering the potential to accelerate demanding simulations such as computa…
physics.flu-dyn2025
Towards scalable surrogate models based on Neural Fields for large scale aerodynamic simulations
Giovanni Catalani, Jean Fesquet, Xavier Bertrand +3
This paper introduces a novel surrogate modeling framework for aerodynamic applications based on Neural Fields. The proposed approach, MARIO (Modulated Aerodynamic Resolution Invar…
cs.LG2025
Geometry aware inference of steady state PDEs using Equivariant Neural Fields representations
Giovanni Catalani, Michael Bauerheim, Frédéric Tost +2
Advances in neural operators have introduced discretization invariant surrogate models for PDEs on general geometries, yet many approaches struggle to encode local geometric struct…