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( Pattern Recognition ) Every node counts: Self-ensembling graph convolutional networks for semi-supervised learning

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SEGCN

Introduction

To capitalize on the information from unlabeled nodes to boost the training for GCN, we propose a novel framework named Self-Ensembling GCN (SEGCN), which marries GCN with Mean Teacher – another powerful model in semi-supervised learning.

Train and Test:

cd segcn

sh train.sh

Result will be saved in ./log.

Results

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( Pattern Recognition ) Every node counts: Self-ensembling graph convolutional networks for semi-supervised learning

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