Machine learning in APOGEE. Identification of stellar populations through chemical abundances
Context. The vast volume of data generated by modern astronomical surveys offers test beds for the application of machine-learning. In these exploratory applications, it is important to evaluate potential existing tools and determine those that are optimal for extracting scientific knowledge from the available observations. Aims: We explore the
Garcia-Dias, Rafael et al.
Advertised on:
9
2019