Learning Graph Topological Features via GAN

Learning Graph Topological Features via GAN

Inspired by the generation power of generative adversarial networks (GANs) in image domains, we introduce a novel hierarchical architecture for learning characteristic topological features from a single arbitrary input graph via GANs. The hierarchical architecture consisting of multiple GANs preserv...

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Bibliographic Details
Main Authors: Weiyi Liu, Pin-Yu Chen, Fucai Yu, Toyotaro Suzumura, Guangmin Hu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Generative adversarial nets
graph analysis
graph generation
Online Access:https://ieeexplore.ieee.org/document/8638941/

Internet

https://ieeexplore.ieee.org/document/8638941/

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