1 citations · 1 across the 3 of their papers we have counts for
3 papers
An End-to-End PyTorch Interface for Differentiable PDE Solvers: A RANS Model-Correction Study
Luca Saverio, Michele Alessandro Bucci, Gianmarco Farro +2
This work presents an end-to-end strategy for solving inverse problems constrained by Partial Differential Equations within a fully differentiable Machine Learning framework. The p…
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…
Agglomeration of Polygonal Grids using Graph Neural Networks with applications to Multigrid solvers
P. F. Antonietti, N. Farenga, E. Manuzzi +2
Agglomeration-based strategies are important both within adaptive refinement algorithms and to construct scalable multilevel algebraic solvers. In order to automatically perform ag…