2 code implementations • NeurIPS 2023 • Artur P. Toshev, Gianluca Galletti, Fabian Fritz, Stefan Adami, Nikolaus A. Adams
Machine learning has been successfully applied to grid-based PDE modeling in various scientific applications.
2 code implementations • 24 May 2023 • Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams
We contribute to the vastly growing field of machine learning for engineering systems by demonstrating that equivariant graph neural networks have the potential to learn more accurate dynamic-interaction models than their non-equivariant counterparts.
no code implementations • 31 Mar 2023 • Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams
We contribute to the vastly growing field of machine learning for engineering systems by demonstrating that equivariant graph neural networks have the potential to learn more accurate dynamic-interaction models than their non-equivariant counterparts.
no code implementations • 25 Jan 2021 • Aaron B. Buhendwa, Stefan Adami, Nikolaus A. Adams
In this work, physics-informed neural networks are applied to incompressible two-phase flow problems.