Bronstein, MichaelGuibas, LeonidasKokkinos, IasonasLitany, OrMitra, NiloyMonti, FedericoRodolà, EmanueleJakob, Wenzel and Puppo, Enrico2019-05-052019-05-0520191017-4656https://doi.org/10.2312/egt.20191036https://diglib.eg.org:443/handle/10.2312/egt20191036In computer graphics and geometry processing, many traditional problems are now becoming increasingly handled by data-driven methods. In an increasing variety of problem settings, deep networks are state-of-the-art, beating dedicated hand-crafted methods by significant margins. This tutorial gives an organized overview of core theory, practice, and graphics-related applications of deep learning.10.2312/egt.2019103643-43