Advances in Graph Neural Networks – PDF/EPUB Version Downloadable
Author(s): Chuan Shi; Xiao Wang; Cheng Yang
Publisher: Springer
ISBN: 9783031161735
Edition:
$49,99
Delivery: This can be downloaded Immediately after purchasing.
Version: Only PDF Version.
Compatible Devices: Can be read on any device (Kindle, NOOK, Android/IOS devices, Windows, MAC)
Quality: High Quality. No missing contents. Printable
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Important: No Access Code
Description
This book provides a comprehensive introduction to the foundations and frontiers of graph neural networks. In addition, the book introduces the basic concepts and definitions in graph representation learning and discusses the development of advanced graph representation learning methods with a focus on graph neural networks. The book providers researchers and practitioners with an understanding of the fundamental issues as well as a launch point for discussing the latest trends in the science. The authors emphasize several frontier aspects of graph neural networks and utilize graph data to describe pairwise relations for real-world data from many different domains, including social science, chemistry, and biology. Several frontiers of graph neural networks are introduced, which enable readers to acquire the needed techniques of advances in graph neural networks via theoretical models and real-world applications.Â
