https://doi.org/10.1051/epjconf/202226500009
Invertible Neural Networks in Astrophysics
1 Universität Heidelberg, Zentrum für Astronomie, Institut für Theoretische Astrophysik, Albert-Ueberle-Str. 2, 69120 Heidelberg, Germany
2 Universität Heidelberg, Interdisziplinäres Zentrum für Wissenschaftliches Rechnen, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
* e-mail: klessen@uni-heidelberg.de
Published online: 7 September 2022
Modern machine learning techniques have become indispensable in many fields of astronomy and astrophysics. Here we introduce a specific class of methods, invertible neural networks, and discuss two specific applications, the prediction of stellar parameters from photometric observations and the study of stellar feedback processes from on emission lines.
© The Authors, Published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
