Deep Learning in Solar Physics

by Andrés Asensio Ramos, IAC

Hosted by Instituto de AstrofĂ­sica de Canarias on September 14, 2017

Abstract

Deep learning has emerged as a very powerful set of techniques to extract relevant information from observations, sometimes showing much better results that other set of finely tuned algorithms. In this contribution I present our efforts in applying deep learning to several problems in Solar Physics, from the estimation of horizontal velocities in the solar surface to fast image reconstruction.