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

This repository allows you to solve forward and inverse problems related to partial differential equations (PDEs) using finite basis physics-informed neural networks (FBPINNs). To improve the ...

Rigorous error estimates for amplitude equations are well known for deterministic PDEs, and there is a large body of literature over the past two decades. However ...

Abstract: Neural differential equations are a promising new member in the neural network family. They show the potential of differential equations for time-series data analysis. In this paper, the ...

Abstract: This paper proposes a novel non-iterative method to solve power system differential algebraic equations (DAEs) using the differential transformation, which is a mathematical tool able to ...

A teenager has just done what dozens of seasoned mathematicians could not: they toppled a conjecture that quietly steered harmonic analysis and ...

Face-to-Face class that meets on designated campus. Students are expected to attend all class meetings on the days and times shown in schedule. Students who do not attend a class meeting by the end of ...

In the present article, fractional view of third order Kortewege-De Vries equations is presented by a sophisticated analytical technique called Mohand decomposition method. The Caputo fractional ...

If you currently have a budget of 200,000 yuan and want to buy a new energy rugged SUV, the popular Deep Blue G318 and ...

If you currently have a budget of 200,000 yuan and want to buy a new energy rugged SUV, the popular Deep Blue G318 and ...

This module focuses on the mathematical modelling of biological phenomena. The emphasis will be on deterministic models based on systems of differential equations. Examples will be drawn from a range ...