Ordinary differential equations (ODEs) and difference equations serve as complementary tools in the mathematical modelling of processes evolving in continuous and discrete time respectively. Together ...

This tutorial presents the application of an R package, RxODE, that facilitates quick, efficient simulations of ordinary differential equation models completely within R. Its application is ...

MR MURRAY'S book is adapted to provide for students that knowledge of the subject of differential equations which they are likely to want in applications of mathematics to physics, and in the general ...

This repository contains an in-depth tutorial to help AI/ML practitioners successfully use neural ordinary differential equations (Neural ODEs or NODEs), understand the mathematics, know which types ...

Congratulations on Your Purchase! This manual celebrates your new Ordinary Differential Equations Solutions Manual By Agarwal and provides a roadmap to its successful operation. Before you begin using ...

A tersely annotated collection of references on types of approaches used in currently available methods to solve the general linear, first-order ordinary differential equation is presented, and ...

ABSTRACT: This paper focuses on the development of a hybrid method with block extension for direct solution of initial value problems (IVPs) of general third-order ordinary differential equations.

Abstract: In this work, we propose a continuous neural network architecture, referred to as Explainable Tensorized Neural - Ordinary Differential Equations (ETN-ODE) network for multi-step time series ...

ABSTRACT: This study focuses on the numerical investigation of fluid flow, heat transfer, and free MHD convection through a semi-infinite vertical porous plate, considering the effects of chemical ...

Abstract: Channel prediction is critical to address the channel aging issue in mobile scenarios. Existing channel prediction techniques are mainly designed for discrete channel prediction, which can ...