An Overview Of Machine Learning In Rotational Spectroscopy
Shipman, Steven
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https://hdl.handle.net/2142/116674
Description
Title
An Overview Of Machine Learning In Rotational Spectroscopy
Author(s)
Shipman, Steven
Issue Date
2022-06-21
Keyword(s)
Mini-symposium: Machine Learning
Abstract
Over the last several years, particularly with the advent of well-documented open source libraries, it has become increasingly easier to apply machine learning techniques to a wide range of problems. Spectroscopy has not been immune to this, and literature searches for ``machine learning" and ``spectroscopy" return thousands of hits. However, these techniques have not yet found widespread use in the area of high-resolution rotational spectroscopy. In this talk, I will give an overview of the current work in the field and highlight some of the challenges that make this a difficult problem. Along the way, I hope to also provide a kind of ``baseline", showing what can be done without the use of machine learning techniques and where they may be particularly applicable.
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