Speaker
Friedrich Anders
(Universitat de Barcelona)
Description
The Gaia mission as well as large-scale ground-based spectroscopic surveys are collecting complex data for millions (even billions) of stars. Within the Gaia group we are therefore been using more and more machine-learning methods to cope with the amount of data. In this talk I will present some examples from recent publications in which we have successfully used supervised (typically regression) and unsupervised (typically dimensionality reduction and clustering) methods in the context of stellar and Galactic astrophysics.
Primary author
Friedrich Anders
(Universitat de Barcelona)
