NeurIPS 2020

Learning Composable Energy Surrogates for PDE Order Reduction

Meta Review

The paper presents a very nice application of ML techniques to a new problem domain and has the potential to open a new research direction. The authors show how to use neural nets to solve a specific class of PDEs in a novel way. Their technique is elegant and more efficient than traditional finite element analysis. The work is well grounded both in ML and the application domain of computational mechanics. The main issues raised by the reviewers concern clarity and they have been addressed in the authors' rebuttal.