The currents of the oceans, the roiling surface of the sun, and the clouds of smoke billowing off a forest fire—all are ...

Abstract: PINNs are neural networks that undergo training to execute supervised learning tasks while adhering to certain laws of physics, which are typically defined by basic nonlinear partial ...

The irregular, swirling motion of fluids we call turbulence can be found everywhere, from stirring in a teacup to currents in the planetary atmosphere. This phenomenon is governed by the Navier-Stokes ...

This repository allows you to solve forward and inverse problems related to partial differential equations (PDEs) using finite basis physics-informed neural networks (FBPINNs). To improve the ...

Abstract: Seismic inversion is a significant tool for exploring the structure and characteristics of the underground. However, the conventional inversion strategy strongly depends on the initial model ...