Understanding molecular abundances in star-forming regions using interpretable machine learning

Author(s):
Heyl, J.; Butterworth, J.J.; Viti, S. (0000-0001-8504-8844)
Published
2023
Publication type
Article / Letter to editor
AstrochemistryMethods: statisticalStars: abundancesAstrophysics - Astrophysics of GalaxiesAstrophysics - Instrumentation and Methods for Astrophysics
Date issued
2023
Language
English
Is part of
Monthly Notices of the Royal Astronomical Society (2023), Vol. 526, no. 1, p. 404-422
hdl
1887/3718876
doi
10.1093/mnras/stad2814
URL
https://ui.adsabs.harvard.edu/abs/2023MNRAS.526..404H