Introduction to Graph Neural Networks
- Computers
- Categories:Computers & Internet
- Language:English(Translation Services Available)
- Publication date:March,2020
- Pages:127
- Retail Price:(Unknown)
- Size:190mm×234mm
- Page Views:197
- Words:(Unknown)
- Star Ratings:
- Text Color:Black and white
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Description
This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN model. Then several variants of the vanilla model are introduced such as graph convolutional networks, graph recurrent networks, graph attention networks, graph residual networks, and several general frameworks. Variants for different graph types and advanced training methods are also included. As for the applications of GNNs, the book categorizes them into structural, non-structural, and other scenarios, and then it introduces several typical models on solving these tasks. Finally, the closing chapters provide GNN open resources and the outlook of several future directions.
Author
Zhiyuan Liu is an associate professor in the Department of Computer Science and Technology, Tsinghua University. He got his B.E. in 2006 and his Ph.D. in 2011 from the Department of Computer Science and Technology, Tsinghua University. His research interests are natural language processing and social computation. He has published over 60 papers in international journals and conferences, including IJCAI, AAAI, ACL, and EMNLP.
Jie Zhou, Tsinghua University
Jie Zhou is a second-year Master's student of the Department of Computer Science and Technology, Tsinghua University. He got his B.E. from Tsinghua University in 2016. His research interests include graph neural networks and natural language processing.
Contents
Basics of Math and Graph
Basics of Neural Networks
Vanilla Graph Neural Networks
Graph Convolutional Networks
Graph Recurrent Networks
Graph Attention Networks
Graph Residual Networks
Variants for Different Graph Types
Variants for Advanced Training Methods
General Frameworks
Applications -- Structural Scenarios
Applications -- Non-Structural Scenarios
Applications -- Other Scenarios
Open Resources
Conclusion
Bibliography
Authors' Biographies