Partial differential equations (PDEs) play a crucial role in scientific computing. Recent advancements in deep learning have led to the development of both data-driven and and Physics-Informed Neural ...

This repository contains the numerical examples for the paper Prediction error certification for PINNs: Theory, computation, and application to Stokes flow [1]. In ...

Abstract: This article develops a methodology employing partial differential equations (PDEs) to facilitate the exponential deployment of large-scale heterogeneous nonlinear multiagent systems (MASs).

GPUs have become a household name in High Performance Computing (HPC) systems over the last 15 years. However, programming GPUs is still largely a manual and arduous task, which requires expert ...

The control of general nonlinear systems is a challenging task in particular for large-scale models as they occur in the semi-discretization of partial differential equations (PDEs) of, say, fluid ...