Can I read Introduction to Graph Neural Networks on EtoBox?

Introduction to Graph Neural Networks by Liu, Zhiyuan is a nonfiction available to read on EtoBox.

What is Introduction to Graph Neural Networks about?

<p><b>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</b>. 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.</p> <p>Graphs are useful data structures in complex real-life applications such as modeling physical systems, learning molecular fingerprints, controlling traffic networks, and recommending friends in social networks. However, these tasks require dealing with non-Euclidean graph data that contains rich relational information between elements and cannot be well handled by traditional deep learning models (e.g., convolutional neural networks (CNNs) or recurrent neural networks (RNNs). Nodes in graphs usually contain useful feature information that cannot be well addressed in most unsupervised representation learning methods (e.g., network embedding methods). Graph neural networks (GNNs) are proposed to combine the feature information and the graph structure to learn better representations on grap

Who reads Introduction to Graph Neural Networks?

Author

Liu, Zhiyuan

Publisher

Morgan & Claypool Publishers 2020

Published

2020

Language

EN

ISBN

9783031015878

Category

nonfiction

Subjects

Mathematics, Science, Computer Science