A PyTorch Implementation of GCN-LPA (arXiv):
Unifying Graph Convolutional Neural Networks and Label Propagation
Hongwei Wang, Jure Leskovec
arXiv Preprint, 2020
GCN-LPA is an end-to-end model that unifies Graph Convolutional Neural Networks (GCN) and Label Propagation Algorithm (LPA) for adaptive semi-supervised node classification.
This repo is going to be done...
The code has been tested running under Python 3.8.1, with the following packages installed (along with their dependencies):
- torch==
- scipy==
- numpy==
- This is not an official implementation.
- Please cite the following papers if you use the code in your work:
@article{kipf2016semi,
title={Semi-Supervised Classification with Graph Convolutional Networks},
author={Kipf, Thomas N and Welling, Max},
journal={arXiv preprint arXiv:1609.02907},
year={2016}
}
@article{wang2020unifying,
title={Unifying Graph Convolutional Neural Networks and Label Propagation},
author={Hongwei Wang and Jure Leskovec},
journal={arXiv preprint arXiv:2002.06755}
year={2020},
}