Course content The course provides an introduction to the theoretical basis for linear partial differential equations, focusing on elliptic equations and eigenvalue problems. The techniques and ...

Course content 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 ...

Learning-based partial differential equations (PDEs), which combine fundamental differential invariants into a nonlinear regressor, have been successfully applied to several computer vision and image ...

5 + Years Experience IT - Software Development Reservoir Engineering Software Specialist Posted: July 04, 2025 ...

Code associated with the paper: Learning data-driven discretizations for partial differential equations. Yohai Bar-Sinai, Stephan Hoyer, Jason Hickey, Michael P. Brenner. Proceedings of the National ...

In this paper, an optimization framework of partial differential neural network combined with divide-space sampling (PDNN-DSS) is proposed to solve the estimation and control problem of 3D ...

Stochastic partial differential equations are proposed in order to model some turbulence phenomena. A particular case (the stochastic Burgers equations) is studied. Global existence of solutions is ...

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

Hannah Cairo has solved the so-called Mizohata-Takeuchi conjecture, a problem in harmonic analysis closely linked to other ...

244 Mathematics Building Buffalo, NY 14260-2900 Phone: (716) 645-6284 Fax: (716) 645-5039 ...