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

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Published inApr 2023

PublisherPackt

ISBN-139781804617526

Edition1st Edition

Concepts

Neural Networks

Author (1)

Maxime Labonne

[1] W. L. Hamilton, R. Ying, and J. Leskovec. Inductive Representation Learning on Large Graphs. arXiv, 2017. DOI: 10.48550/ARXIV.1706.02216.
[2] R. Ying, R. He, K. Chen, P. Eksombatchai, W. L. Hamilton, and J. Leskovec. Graph Convolutional Neural Networks for Web-Scale Recommender Systems. Jul. 2018. DOI: 10.1145/3219819.3219890.
[3] Ankit Jain. Food Discovery with Uber Eats: Using Graph Learning to Power Recommendations: https://www.uber.com/en-US/blog/uber-eats-graph-learning/.
[4] Galileo Mark Namata, Ben London, Lise Getoor, and Bert Huang. Query-Driven Active Surveying for Collective Classification. International Workshop on Mining and Learning with Graphs. 2012.
[5] M. Agrawal, M. Zitnik, and J. Leskovec. Large-scale analysis of disease pathways in the human interactome. Nov. 2017. DOI: 10.1142/9789813235533_0011.
[6] W.-L. Chiang, X. Liu, S. Si, Y. Li, S. Bengio, and C.-J. Hsieh. Cluster-GCN. Jul. 2019. DOI: 10.1145/3292500.3330925...

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Hands-On Graph Neural Networks Using Python

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

Author (1)

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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