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

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), ...

TensorFlow implementation for DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations. Physics-informed neural networks are a type of promising tools to ...

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 ...

The math of even the simplest ocean waves is notoriously uncooperative. A team of Italian mathematicians has made major ...

From industrial robots to self-driving cars, engineers face a common problem: keeping machines steady and predictable. When ...

Ask the publishers to restore access to 500,000+ books. An icon used to represent a menu that can be toggled by interacting with this icon. A line drawing of the Internet Archive headquarters building ...

Abstract: This article is devoted to present a framework for studying type-2 fuzzy calculus. Some new concepts pertaining to interval type-2 fuzzy functions (IT2FF) and interval type-2 fuzzy ...

New CRCs focus on software security, electrocatalysts for carbon recycling, isotope geochemistry, quantum systems, and ...