Batch virtual adversarial training for graph convolutional networks

Batch virtual adversarial training for graph convolutional networks

We present batch virtual adversarial training (BVAT), a novel regularization method for graph convolutional networks (GCNs). BVAT addresses the issue that GCNs do not ensure the smoothness of the model’s output distribution against local perturbations around the input node features. We propose two a...

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Bibliographic Details
Main Authors:	Zhijie Deng, Yinpeng Dong, Jun Zhu
Format:	Article
Language:	English
Published:	KeAi Communications Co. Ltd. 2023-01-01
Series:	AI Open
Subjects:	Virtual adversarial training Graph convolutional networks Semi-supervised node classification
Online Access:	http://www.sciencedirect.com/science/article/pii/S2666651023000098

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