From a technical point of view, the internal structure of the library is pretty cool -- all kinds of equations (ODEs, SDEs, CDEs) are solved in a unified way (rather than being treated separately), ...

Ask the publishers to restore access to 500,000+ books. Can You Chip In? We’re celebrating our 1 trillionth archived web page. If you find our library useful, learn how you can help us fundraise! Can ...

Abstract: Acoustic wave equation is typically the starting point in mathematical modeling of sound propagation, scattering, and diffraction as well as in solving inverse problems attendant to acoustic ...

This paper presents In-Context Operator Networks (ICON), a neural network approach that can learn new operators from prompted data during the inference stage without requiring any weight updates.

Despite their success, the above methods are designed to solve problems with a specific differential equation. The neural network needs to be trained again when the terms in the equation or the ...

School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China. Fractional differential equations have been widely used to describe complex problems in science ...

In this paper, the boundary value problems for second order singularly perturbed delay differential equations are treated. A generic numerical approach based on finite difference is presented to solve ...

The research paper aims to investigate the space-time fractional cubic-quartic non-linear Schrödinger equation in the appearance of the third, and fourth-order dispersion impacts without both group ...

If today's college students could find a way to get their hands on a copy of Facebook's latest neural network, they could cheat all the way through Calc 3. They could even solve the differential ...

Abstract: The method of Davie’s [5] describes an easily generated scheme based on the standard order-one Milstein scheme, which is order-one in the Vaserstein metric, provided that the stochastic ...