Deep Learning in Solar Physics

by Andrés Asensio Ramos, IAC

Hosted by Instituto de AstrofĂ­sica de Canarias on September 21, 2017


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.


Seminar video (The first few minutes are missing.)