Structural reinforcement-based graph convolutional networks

Structural reinforcement-based graph convolutional networks

Graph Convolutional Network (GCN) is a tool for feature extraction, learning, and inference on graph data, widely applied in numerous scenarios. Despite the great success of GCN, it performs weakly under some application conditions, such as a multiple layers model or severely limited labeled nodes....

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Bibliographic Details
Main Authors: Jisheng Qin, Qianqian Wang, Tao Tao
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Connection Science
Subjects:
graph convolutional network
structural reinforcement
semantic alignment
Online Access:http://dx.doi.org/10.1080/09540091.2022.2151977

Internet

http://dx.doi.org/10.1080/09540091.2022.2151977

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