Concepts and Techniques of Graph Neural Networks

Concepts and Techniques of Graph Neural Networks
Author :
Publisher : IGI Global
Total Pages : 267
Release :
ISBN-10 : 9781668469057
ISBN-13 : 1668469057
Rating : 4/5 (057 Downloads)

Book Synopsis Concepts and Techniques of Graph Neural Networks by : Kumar, Vinod

Download or read book Concepts and Techniques of Graph Neural Networks written by Kumar, Vinod and published by IGI Global. This book was released on 2023-05-22 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Concepts and Techniques of Graph Neural Networks Related Books

Concepts and Techniques of Graph Neural Networks
Language: en
Pages: 267
Authors: Kumar, Vinod
Categories: Computers
Type: BOOK - Published: 2023-05-22 - Publisher: IGI Global

DOWNLOAD EBOOK

Recent advancements in graph neural networks have expanded their capacities and expressive power. Furthermore, practical applications have begun to emerge in a
Graph Neural Networks: Foundations, Frontiers, and Applications
Language: en
Pages: 701
Authors: Lingfei Wu
Categories: Computers
Type: BOOK - Published: 2022-01-03 - Publisher: Springer Nature

DOWNLOAD EBOOK

Deep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data
Graph Representation Learning
Language: en
Pages: 141
Authors: William L. William L. Hamilton
Categories: Computers
Type: BOOK - Published: 2022-06-01 - Publisher: Springer Nature

DOWNLOAD EBOOK

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational induct
Deep Learning on Graphs
Language: en
Pages: 339
Authors: Yao Ma
Categories: Computers
Type: BOOK - Published: 2021-09-23 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A comprehensive text on foundations and techniques of graph neural networks with applications in NLP, data mining, vision and healthcare.
A Wavelet Tour of Signal Processing
Language: en
Pages: 663
Authors: Stephane Mallat
Categories: Computers
Type: BOOK - Published: 1999-09-14 - Publisher: Elsevier

DOWNLOAD EBOOK

This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from materi