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Introduction to graph neural networks

By: Contributor(s): Material type: TextTextSeries: 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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Item type Current library Collection Call number Status Date due Barcode
Book 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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