Invertible Neural Networks in Astrophysics

Abstract

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.