Meta-MgNet: Meta Multigrid Networks for Solving Parameterized Partial Differential Equations

Understand

This paper studies numerical solutions for parameterized partial differential equations (P-PDEs) with deep learning (DL).

• P-PDEs arise in many important application areas and the computational cost using traditional numerical schemes can be exorbitant, especially when the parameters fall into a particular range and the underlying PDE is required to be solved with high accuracy.
• Recently, solving PDEs with DL has become an emerging field.
• Existing works demonstrate great potentials of the DL based approach in speeding up numerical solutions of PDEs.