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Implementation of GNN

PyTorch implementation of Graph Convolutional Networks (GCN) and Deep Graph CNN (DGCNN)

Reference Papers

GCN is based on the paper presented in ICLR 2017:

DGCNN is based on the paper presented in AAAI 2018:

Requirements

  • PyTorch
  • PyTorch Geometric

Datasets

This implementation uses the Lab dataset which includes two classes:

  • Benign
  • Mirai

Results

The results of the implementation are shown in the following table:

Detector Training Accuracy Testing Accuracy
GCN 99.43% 99.36%
DGCN 99.56% 99.53%

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PyTorch implementation GCN and DGCNN paper

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