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Graph Neural Network Basics. Models and Applications(Chinese Edition)
Published by Tsinghua University Press, 2024
ISBN 10: 7302658838 ISBN 13: 9787302658832
Language: English
US$ 114.42
Convert currencyUS$ 18.00 shipping from China to U.S.A.Quantity: 1 available
Add to basketpaperback. Condition: New. Paperback. Pub Date: 2024-04 Pages: 212 Publisher: Tsinghua University Press Graph neural networks can not only solve graph data problems that traditional machine learning methods cannot solve. but can also be applied to many practical scenarios. such as social networks. drug discovery. network security. financial risk control. etc. This book aims to provide a detailed and comprehensive introductory guide for beginners and practitioners. focusing on the basics. models. and practical applicati.
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Graph Neural Network: Basics and Frontiers (Full Color) (Produced by Blog Post)(Chinese Edition)
Published by Electronic Industry Press, 2021
ISBN 10: 7121405024 ISBN 13: 9787121405020
Language: Chinese
US$ 114.42
Convert currencyUS$ 18.00 shipping from China to U.S.A.Quantity: 3 available
Add to basketpaperback. Condition: New. Paperback. Pub Date: 2021-02-01 Pages: 152 Language: Chinese Publisher: Publishing House of Electronics Industry Graph Neural Network is an emerging direction in the field of artificial intelligence. It has not only quickly received widespread attention from the academic community. but also has been successfully applied In many areas of industry.?This book introduces the basic knowledge and cutting-edge research of graph neural networks and graph deep learning. not only their development hist.
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US$ 205.90
Convert currencyUS$ 18.00 shipping from China to U.S.A.Quantity: 3 available
Add to basketpaperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2022-11-01 Pages: 516 Publisher: People's Posts and Telecommunications Press This book is dedicated to introducing the basic concepts and algorithms of graph neural networks. research frontiers. and extensive and emerging applications. covering a wide range of topics in graph neural networks. From basics to frontiers. from methods to applications. it involves everything from methodology to application scenarios. The book is divided into four parts: the fi.
