This repository is the official implementation of Graph Alignment Kernels using Weisfeiler and Leman Hierarchies.
Code is written in Python 3.6 and requires:
- NetworkX 2
- sklearn 0.23
Download the datasets from here: https://chrsmrrs.github.io/datasets/docs/datasets/ and then extract them into the "datasets" folder
To create the kernel matrix and then perform 10-fold cross validation, first specify the dataset and the hyperparameter T in the main.py file and then execute:
python main.py
Please cite our paper if you use this code:
@inproceedings{nikolentzos2023graph,
title={Graph Alignment Kernels using Weisfeiler and Leman Hierarchies},
author={Nikolentzos, Giannis and Vazirgiannis, Michalis},
booktitle={Proceedings of the 26th International Conference on Artificial Intelligence and Statistics},
pages={2019--2034},
year={2023}
}