Introduction to Graph Neural Networks

丛 书 名：Synthesis Lectures on Artificial Intelligence and Machine Learning

版本说明：1

作     者：Zhiyuan Liu Jie Zhou 

I S B N：(纸本) 9783031004599 

出 版 社：Springer Cham 

出 版 年：1000年

页      数：XVII, 109页

主 题 词：Artificial Intelligence Machine Learning Mathematical Models of Cognitive Processes and Neural Networks 

摘      要：This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN model. Then several variants of the vanilla model are introduced such as graph convolutional networks, graph recurrent networks, graph attention networks, graph residual networks, and several general frameworks. Variants for different graph types and advanced training methods are also included. As for the applications of GNNs, the book categorizes them into structural, non-structural, and other scenarios, and then it introduces several typical models on solving these tasks. Finally, the closing chapters provide GNN open resources and the outlook of several future directions.