Graph Neural Networks : Graph Representation Learning using Neural Networks

Abstract

This book, "Graph Neural Networks: Graph Representation Learning with a Neural Network Approach," offers a comprehensive and up-to-date guide to the dynamic field of Graph Neural Networks (GNNs). It serves as an essential Persian-language resource for students, researchers, and AI practitioners. Starting from the fundamental concepts of graph theory, the book progressively advances to cover sophisticated architectures and modern techniques. Key topics include graph convolutional networks (GCN and ChebNet), graph attention networks (GAT and GATv2), message-passing networks, and graph pooling methods.