1 code implementation • 23 Mar 2022 • Shawn G. Rosofsky, Hani Al Majed, E. A. Huerta
We present an end-to-end framework to learn partial differential equations that brings together initial data production, selection of boundary conditions, and the use of physics-informed neural operators to solve partial differential equations that are ubiquitous in the study and modeling of physics phenomena.
