Three-channel Residual Graph Convolutional Network for Semi-supervised Node Classification
Author:
Affiliation:
1. Beijing University of Chemical Technology,College of Information Science & Technology,Beijing,China
2. Macao Polytechnic University,Faculty of Applied Sciences,Macao SAR,P.R.China,999078
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10587298/10587321/10587972.pdf?arnumber=10587972
Reference15 articles.
1. The Graph Neural Network Model
2. Semi-supervised classification with graph convolutional networks;Kipf,2016
3. DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification
4. Towards Clustering-friendly Representations
5. Adaptive Graph Convolutional Neural Networks
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