Nicola De Cao: “Deep Generative Models for Molecular Graphs“

Machine Learning for Physics and the Physics of Learning 2019 Workshop I: From Passive to Active: Generative and Reinforcement Learning with Physics “Deep Generative Models for Molecular Graphs“ Nicola De Cao, University of Amsterdam Abstract: Deep generative models are a rapidly advancing area of research in machine learning. They recently have been proven to effectively deal with continuous Euclidean data such as sounds, images, and videos. However, how to generate non-Euclidean and structured abstract