An Introduction to Using Software Tools for Automatic Differentiation
Uwe Naumann, Andrea Walther
TL;DR
This paper provides a beginner-friendly overview of software tools for automatic differentiation, including practical examples and resources, aimed at helping newcomers adopt AD technology effectively.
Contribution
It offers an accessible introduction to AD software tools with practical examples and links, facilitating easier adoption for new users.
Findings
Practical examples demonstrate how to use AD tools effectively.
Resources and links are provided for further learning.
The document is regularly updated to reflect software evolution.
Abstract
We give a gentle introduction to using various software tools for automatic differentiation (AD). Ready-to-use examples are discussed, and links to further information are presented. Our target audience includes all those who are looking for a straightforward way to get started using the available AD technology. The document is dynamic in the sense that its content will be updated as the AD software evolves.
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Taxonomy
TopicsControl Systems and Identification · Matrix Theory and Algorithms · Numerical methods for differential equations