  The need for accurate photometric redshifts estimation is a topic that has
fundamental importance in Astronomy, due to the necessity of efficiently
obtaining redshift information without the need of spectroscopic analysis. We
propose a method for determining accurate multimodal photo-z probability
density functions (PDFs) using Mixture Density Networks (MDN) and Deep
Convolutional Networks (DCN). A comparison with a Random Forest (RF) is
performed.
