Partial differential equations (PDEs) are a class of mathematical problems that represent the interplay of multiple variables ...

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential ...

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R ...

input, hidden, and output, by which one can process the information at hand. As such, this chapter includes the idea of ANN with the steepest descent search optimization technique to solve ordinary ...

Partial differential equations (PDEs) are a class of mathematical problems that represent the interplay of multiple variables, and therefore have ...

Abstract: In this paper, the concept of multirate partial differential equations (MPDEs) is applied to obtain an efficient solution for nonlinear low-frequency electrical circuits with pulsed ...

The Abel prizewinner’s pragmatic approach to solving differential equations was influential across fields ranging from ...

The course provides a thorough introduction to design, analysis (both theoretical and empirical), and programming of difference and elemental methods to solve differential equations. In addition, the ...