Introduction to graph neural networks
Material type: TextSeries: Synthesis Lectures on Artificial Intelligence and Machine LearningPublication details: California Morgan & Claypool Publishers 2020Description: xvii, 109pISBN:- 9781681737652 (pbk.)
- 006.32 LIU
Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
Book | Plaksha University Library | Computer science | 006.32 LIU (Browse shelf(Opens below)) | Checked out | 13/12/2023 | 002995 |
Browsing Plaksha University Library shelves, Collection: Computer science Close shelf browser (Hides shelf browser)
006.3122 HAS The elements of statistical learning : data mining inference and prediction | 006.32 HAY Neural networks and learning machines | 006.32 HUY Handbook of neural network signal processing | 006.32 LIU Introduction to graph neural networks | 006.32 SIV Introduction to neural networks using MATLAB 6.0 | 006.32 YEG Artificial neural networks | 006.32 ZAH Fuzzy logic for the management of uncertainty |
https://www.morganclaypool.com/loi/aim
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.
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