• Title: Introduction to Graph Neural Networks for Machine Learning Engineers
• Author(s) James H. Tanis, Chris Giannella, Adrian V. Mariano, Daoud Meerzaman
• Publisher: arXiv (2026); eBook (Creative Commons Licensed)
• License(s): Creative Commons License (CC)
• Hardcover/Paperback: N/A
• eBook: PDF
• Language: English
• ISBN-10: N/A
• ISBN-13: N/A
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Book Description

Graph Neural Networks (GNN) are deep neural networks designed for graphs with attributes attached to nodes or edges. This survey introduces graph neural networks through the encoder-decoder framework and provides examples of decoders for a range of graph analytic tasks.

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• Neural Networks
• Deep Learning
• Machine Learning
• Graph Theory

• Introduction to Graph Neural Networks for Machine Learning Engineers (James H. Tanis, et al.)
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