Concepts and Techniques of Graph Neural Networks (Paperback)

Recent advancements in graph neural networks have expanded their capacities and expressive power. Furthermore, practical applications have begun to emerge in a variety of fields including recommendation systems, fake news detection, traffic prediction, molecular structure in chemistry, antibacterial discovery physics simulations, and more. As a result, a boom of research at the juncture of graph theory and deep learning has revolutionized many areas of research. However, while graph neural networks have drawn a lot of attention, they still face many challenges when it comes to applying them to other domains, from a conceptual understanding of methodologies to scalability and interpretability in a real system. Concepts and Techniques of Graph Neural Networks provides a stepwise discussion, an exhaustive literature review, detailed analysis and discussion, rigorous experimentation results, and application-oriented approaches that are demonstrated with respect to applications of graph neural networks. The book also develops the understanding of concepts and techniques of graph neural networks and establishes the familiarity of different real applications in various domains for graph neural networks. Covering key topics such as graph data, social networks, deep learning, and graph clustering, this premier reference source is ideal for industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

General

Imprint:	IGI Global
Country of origin:	United States
Release date:	June 2023
First published:	2023
Editors:	Vinod Kumar • Dharmendra Singh Rajput
Dimensions:	279 x 216mm (L x W)
Format:	Paperback
Pages:	320
ISBN-13:	978-1-66846-904-0
Categories:	Books
LSN:	1-66846-904-9
Barcode:	9781668469040

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