Deep Learning on Graphs

In the last decade, deep learning has been a ‘crown jewel’ in artificial intelligence and machine learning. However, utilizing deep learning methods for analyzing the ubiquitous graph data is a non-trivial problem, which attracted considerable research attention in the past few years. In this talk, I will present the categorization of graph-based deep learning methods and review these methods following their history of developments and how these methods solve challenges of graphs. The differences of these models and how to composite different architectures will also be discussed. Finally, I will discuss potential future directions. More details can be found in our survey paper: https://arxiv.org/abs/1812.04202.