Introduction to graph neural networks

By:

Liu, Zhiyuan

Contributor(s):

Zhou, Jie

Material type: Text

TextSeries: Synthesis Lectures on Artificial Intelligence and Machine LearningPublication details: California Morgan & Claypool Publishers 2020Description: xvii, 109pISBN:

9781681737652 (pbk.)

Subject(s):

DDC classification:

006.32 LIU

Summary: 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.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Plaksha University Library	Computer science	006.32 LIU (Browse shelf(Opens below))	Checked out	13/12/2023	002995

https://www.morganclaypool.com/loi/aim

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.

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