Several fundamental results on the existence and behavior of solutions to semilinear functional differential equations are developed in a Banach space setting. The ideas are applied to ...

Abstract: Many problems in science and engineering can be mathematically modeled using partial differential equations (PDEs), which are essential for fields like computational fluid dynamics (CFD), ...

Abstract: Based on deep neural network, elliptic partial differential equations in complex regions are solved. Accurate and effective strategies and numerical methods for elliptic partial differential ...

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Listen to the full series on BBC Sounds. Individual particles do not have the same properties as the bulk substance. The physical properties are due to the arrangement and movement of all the ...

This repository contains code for Graph Neural ODE++. This work was completed as part of CPSC 483: Deep Learning on Graph-Structured Data. We propose Graph Neural ODE++, an improved paradigm for Graph ...

Solving partial differential equations (PDEs) is a required step in the simulation of natural and engineering systems. The associated computational costs significantly increase when exploring various ...

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Please see the Module Guides section on the Course Structure and Content pages of the Department of Mathematics for details on this module.

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