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...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8638941/ |