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Exploring Deep Learning Architectures for Graph Applications

Name: Exploring Deep Learning Architectures for Graph Applications
Brand: LAP LAMBERT Academic Publishing
SKU: 36917993
Price: 21503 HUF
Availability: InStock
Author: Irwin King
ISBN: 9786202917650

Irwin King

Language

English

Book Paperback

Libristo code: 36917993

Publishers LAP LAMBERT Academic Publishing, October 2020

Graph-structured data are the backbone of numerous real-world machine learning tasks, such as social... Full description

Libristo code: 36917993

146 b

21 503 Ft

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Graph-structured data are the backbone of numerous real-world machine learning tasks, such as social networks, recommender systems, traffic networks, and so on. The fundamental challenge in solving these tasks is to find a way to encode graph structures as well as to incorporate various node or edge information so that machine learning models can easily exploit them. In this dissertation, we explore deep learning architectures, especially the graph neural networks for multiple graph learning applications, i.e., node classification, link prediction, spatiotemporal graph forecasting on irregular grid, and supervised sequence learning problems.