An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In chemical reaction network theory, ordinary differential equations are used to model ...

We produce an alternate proof of the extended binomial theorem by solving a first order linear ordinary differential equation with a given initial condition. The method is easy to follow and the ...

This course provides an introduction to topics involving ordinary differential equations. Emphasis is placed on the development of abstract concepts and applications for first-order and linear ...

Abstract: Recently, numerical solutions for Ordinary Differential Equations (ODEs) based on fourth-order Runge-Kutta method and fast Euler method are becoming more popular, however, necessary large ...

Abstract: Aiming to solve the ordinary differential equations that often appear in the scientific calculation, the solution method is studied using a machine learning algorithm. A method of ...

‘A’ ordinary shares are a class of ordinary shares that may carry different rights and privileges compared to other classes of shares within the same company. ‘A’ ordinary shares are a type of equity ...

A computational revolution unleashed the power of artificial neural networks. At the heart of that revolution is automatic differentiation, which calculates the derivative of a performance measure ...

Kinetic modeling has relied on using a tedious number of mathematical equations to describe molecular kinetics in interacting reactions. The long list of differential equations with associated ...