@inbook{20e63ad6d45043da9553c23b0de7dcae,
title = "Machine Learning for Combustion Chemistry",
abstract = "Machine learning provides a set of new tools for the analysis, reduction and acceleration of combustion chemistry. The implementation of such tools is not new. However, with the emerging techniques of deep learning, renewed interest in implementing machine learning is fast growing. In this chapter, we illustrate applications of machine learning in understanding chemistry, learning reaction rates and reaction mechanisms and in accelerating chemistry integration.",
author = "T. Echekki and A. Farooq and M. Ihme and Sarathy, {S. M.}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
doi = "10.1007/978-3-031-16248-0_5",
language = "English (US)",
series = "Lecture Notes in Energy",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "117--147",
booktitle = "Lecture Notes in Energy",
address = "Germany",
}