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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.
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Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

activation function 107

Adamic-Adar index 165

adjacency list 22

adjacency matrix 20-22

adjacent 18

aggregate function 148

aggregation 129

aggregator 129

LSTM aggregator 129

mean aggregator 129

pooling aggregator 129

anomaly detection 275

A* search 25

attention scores 106

Attention Temporal Graph Convolutional Network (A3T-GCN)

implementing 267-273

autoregressive models 190, 191

average precision (AP) 169

averaging 108

B

batch gradient descent 126

Bayesian Personalized Ranking (BPR) 309

BERT 105

betweenness centrality 19, 20

bidirectional BFS 24

binary bag of words 68

BookCrossing community

URL 296

Book-Crossing dataset 296-302

preprocessing 302-305

breadth-first search (BFS) 11, 23, 51

implementing...

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Published in: Apr 2023Publisher: PacktISBN-13: 9781804617526
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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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