MECH.5200 — Graduate Id: 036063 Offering: 1 Credits: 3-3 Description Mathematical approaches for numerically solving partial differential equations. The focus will be (a) iterative solution methods ...

Exponential integrators represent an innovative class of numerical methods designed to address the challenges posed by stiff differential equations.

A new method, combining complex analysis with numerics, is introduced for solving a large class of linear partial differential equations (PDEs). This includes any linear constant coefficient PDE, as ...

The research of the institute focuses on the construction, analysis and implementation of efficient numerical methods and algorithms for solving practical and complex problems arising from various ...

Continuation of APPM 4650. Examines numerical solution of initial-value problems and two-point boundary-value problems for ordinary differential equations. Also looks at numerical methods for solving ...

Two new approaches allow deep neural networks to solve entire families of partial differential equations, making it easier to model complicated systems and to do so orders of magnitude faster.

Porous-DeepONet, a novel deep learning framework, efficiently solves parameterized PDEs in porous media by capturing complex features using convolutional neural networks. It significantly ...