Graph Neural Networks Lecture
Network theory has very many application areas, where graphs are of primary importance, in e.g.,:
-Communication networks
-Epidemiology
-Systems Biology
-Social networks.
Social Media (e.g., Twitter, Facebook, Instagram, to name a few) has had a tremendous growth in the past 20 years. Social Media Analysis has very many applications, e.g.,:
-Recommendation Systems
-Sentiment Analysis
-Information Diffusion
-Web Search.
This lecture overviews Graph Neural Networks that has many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Introduction to Graphs. Neural Networks. Graph Convolutional Networks (GCN). Recurrent Graph Neural Networks (RGNN). Graph Auto-Encoders. Spatial-Temporal Graph Neural Networks. GNN Applications.