Learning and solving governing equations of a physical system from data is a central challenge in a variety of areas of science and engineering. These governing equations are usually represented by ...

Solving partial differential equations (PDEs) with numerical methods has a pivotal role in a wide variety of disciplines in science and engineering, with applications such as topology and design ...

Two new approaches allow deep neural networks to solve entire families of partial differential equations, making it easier to model complicated systems and to do so orders of magnitude faster. In high ...