An extensible Benchmarking Graph-Mesh dataset for studying Steady-State Incompressible Navier-Stokes Equations. (arXiv:2206.14709v1 [cs.LG])

Recent progress in \emph{Geometric Deep Learning} (GDL) has shown its
potential to provide powerful data-driven models. This gives momentum to
explore new methods for learning physical systems governed by \emph{Partial
Differential Equations} (PDEs) from Graph-Mesh data. However, despite the
efforts and recent achievements, several research directions remain unexplored
and progress is still far from satisfying the physical requirements of
real-world phenomena. One of the major impediments is the absence of
benchmarking datasets and common physics evaluation protocols. In this paper, …

arxiv benchmarking dataset graph lg mesh state studying