A new technical paper titled “Solving sparse finite element problems on neuromorphic hardware” was published by researchers at Sandia National Lab. “The finite element method (FEM) is one of the most ...
Discover how this powerful open-source SPICE simulator helps you analyse and validate analog, digital and mixed-signal ...
Most courses in the department fall into one or more of the following categories. Please choose the appropriate category and then the appropriate course, where you will find some or all of the ...
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential ...
The PIML4PDE framework is designed to solve Partial Differential Equations (PDEs) using Physics-Informed Machine Learning (PIML). This framework is intended for educational purposes, demonstrating ...
Abstract: Zeroing neural networks (ZNNs) play a crucial role in efficiently solving time-varying problems. Recently, ZNNs are integrated with many advanced control theories with a certain convergence ...
Abstract: This letter explores the stabilization of a wide class of coupled dynamical systems, consisting of partial and ordinary differential equations with spatially varying coefficients. The main ...
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