The Rise of Graph Neural Networks

This chapter explores the evolution and increasing significance of graph neural networks in machine learning, highlighting their transition from niche to mainstream within the research community. It addresses the challenges and advancements in large-scale graph learning, including the introduction of benchmarks like OpenGraph, and their real-world applications in industries such as healthcare and social networks. The discussion also delves into the intersection of deep learning with geometric data and the ongoing research tackling adversarial challenges and temporal modeling for dynamic graphs.