Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex mathematical problems that underpin scientific and engineering challenges.

Abstract: There has been significant recent work on solving PDEs using neural networks on infinite dimensional spaces. In this talk we consider two examples. First, we prove that transformers can ...

In the fields of physics, mathematics, and engineering, partial differential equations (PDEs) are essential for modeling various phenomena, from heat diffusion to particle motion and wave propagation.

A new article notes that journal articles reporting how well machine learning models solve certain kinds of equations are often overly optimistic. The researchers suggest two rules for reporting ...

Under the hood, multiphysics software based on the finite-element (FE) method mathematically models complex engineering and scientific problems in inductive heating, heat transfer, and ...