9 citations · 17 across the 5 of their papers we have counts for
5 papers
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…
PLAID: A Unified Data Model for Machine Learning on Heterogeneous Physics Simulations
Fabien Casenave, Xavier Roynard, Brian Staber +17
Machine learning-based surrogate models have emerged as a powerful tool to accelerate simulation-driven scientific workflows, but their adoption is limited by the lack of large-sca…
Optimal morphings for model-order reduction for poorly reducible problems with geometric variability
Abbas Kabalan, Fabien Casenave, Felipe Bordeu +2
We propose a new model-order reduction framework to poorly reducible problems arising from parametric partial differential equations with geometric variability. In such problems, t…
Elasticity-based morphing technique and application to reduced-order modeling
Abbas Kabalan, Fabien Casenave, Felipe Bordeu +2
The aim of this article is to introduce a new methodology for constructing morphings between shapes that have identical topology. The morphings are obtained by deforming a referenc…
Leader-Follower Synchronization of a Network of Boundary-Controlled Parabolic Equations With In-Domain Coupling
Abbas Kabalan, Francesco Ferrante, Giacomo Casadei +2
In this letter, we study the leader-synchronization problem for a class of partial differential equations with boundary control and in-domain coupling. We describe the problem in a…