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You're reading from  Hands-On Graph Neural Networks Using Python

Product typeBook
Published inApr 2023
PublisherPackt
ISBN-139781804617526
Edition1st Edition
Concepts
Neural Networks
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Author (1)
Maxime Labonne
Maxime Labonne
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Maxime Labonne

Maxime Labonne is currently a senior applied researcher at Airbus. He received a M.Sc. degree in computer science from INSA CVL, and a Ph.D. in machine learning and cyber security from the Polytechnic Institute of Paris. During his career, he worked on computer networks and the problem of representation learning, which led him to explore graph neural networks. He applied this knowledge to various industrial projects, including intrusion detection, satellite communications, quantum networks, and AI-powered aircrafts. He is now an active graph neural network evangelist through Twitter and his personal blog.
Read more about Maxime Labonne

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Introducing graph properties

In graph theory, a graph is a mathematical structure consisting of a set of objects, called vertices or nodes, and a set of connections, called edges, which link pairs of vertices. The notation is used to represent a graph, where is the graph, is the set of vertices, and is the set of edges.

The nodes of a graph can represent any objects, such as cities, people, web pages, or molecules, and the edges represent the relationships or connections between them, such as physical roads, social relationships, hyperlinks, or chemical bonds.

This section provides an overview of fundamental graph properties that will be used extensively in later chapters.

Directed graphs

One of the most basic properties of a graph is whether it is directed or undirected. In a directed graph, also called a digraph, each edge has a direction or orientation. This means that the edge connects two nodes in a particular direction, where one node is the source and the other...

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Hands-On Graph Neural Networks Using Python
Published in: Apr 2023Publisher: PacktISBN-13: 9781804617526
© 2023 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Maxime Labonne

Maxime Labonne is currently a senior applied researcher at Airbus. He received a M.Sc. degree in computer science from INSA CVL, and a Ph.D. in machine learning and cyber security from the Polytechnic Institute of Paris. During his career, he worked on computer networks and the problem of representation learning, which led him to explore graph neural networks. He applied this knowledge to various industrial projects, including intrusion detection, satellite communications, quantum networks, and AI-powered aircrafts. He is now an active graph neural network evangelist through Twitter and his personal blog.
Read more about Maxime Labonne

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