A convolutional neural network for graph classification in PyTorch
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fix for #6 Accuracy = 0 as a result of recent PyTorch changes. See here for info: pytorch/pytorch#5411
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README.md

Kernel Graph Convolutional Neural Networks

Code for the paper Kernel Graph Convolutional Neural Networks.

Requirements

Code is written in Python 3.6 and requires:

  • PyTorch 0.3
  • NetworkX 1.11
  • igraph 0.7
  • scikit-learn 0.18

Datasets

Use the following link to download datasets:

https://ls11-www.cs.tu-dortmund.de/staff/morris/graphkerneldatasets

Extract the datasets into the datasets folder.

Run the model

First, specify the dataset and the hyperparameters in the main.py file. Then, use the following command:

$ python main.py

Cite

Please cite our paper if you use this code:

@inproceedings{nikolentzos2018kernel,
  title={Kernel Graph Convolutional Neural Networks},
  author={Nikolentzos, Giannis and Meladianos, Polykarpos and Tixier, Antoine Jean-Pierre and Skianis, Konstantinos and Vazirgiannis, Michalis},
  booktitle={International Conference on Artificial Neural Networks},
  pages={22--32},
  year={2018},
  organization={Springer}
}

Provided for academic use only