https://github.com/Eilene/GWNN

A TensorFlow implementation of Graph Wavelet Neural Network
https://github.com/Eilene/GWNN

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A TensorFlow implementation of Graph Wavelet Neural Network

• Host: GitHub
• URL: https://github.com/Eilene/GWNN
• Owner: Eilene
• Created: 2019-01-28T02:02:44.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-01-28T15:01:17.000Z (over 5 years ago)
• Last Synced: 2024-05-21T17:21:39.948Z (4 months ago)
• Language: Python
• Homepage:
• Size: 5.6 MB
• Stars: 63
• Watchers: 2
• Forks: 18
• Open Issues: 6
• Metadata Files:
  • Readme: readme.md

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• awesome-network-embedding - [Python TensorFlow

README

        
## Graph Wavelet Neural Network

> Graph Wavelet Neural Network. Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng. ICLR, 2019. [pdf](https://openreview.net/pdf?id=H1ewdiR5tQ)

## Overview



 



> We provide a TensorFlow implementation of Graph Wavelet Neural Network, which implements graph convolution via graph wavelet transform instead of Fourier transform. Different from graph Fourier transform, graph wavelets are sparse and localized in vertex domain, offering high efficiency and good interpretability for graph convolution. We evaluated our model in the task of graph-based semi-supervised classification.

## Requirements

the script has been tested running under Python 2.7, with the following packages installed (along with their dependencies):

* tensorflow==0.12.0

* numpy==1.14.0

* scipy==0.19.1

* networkx==2.0

## Run the Code

* cd GraphWaveletNetwork

* python train.py

## Parameters

* --wavelet_s                 FLOAT         wavelet scaling parameter.                  Default: Cora: 1.0, Citeseer: 0.7, Pubmed: 0.5

* --threshold                 FLOAT         threshold parameter for wavelet.            Default: Cora: 1e-4, Citeseer: 1e-5, Pubmed: 1e-7

* --epochs                    INT           Number of Adam epochs.                      Default: 1000.

* --early-stopping            INT           Number of early stopping epochs.            Default: 100.

## Run Example

The run example for Cora dataset in default parameter



 



## Cite

Please cite our paper if you use this code in your own work:

> @inproceedings{

xu2018graph,

title={Graph Wavelet Neural Network},

author={Bingbing Xu and Huawei Shen and Qi Cao and Yunqi Qiu and Xueqi Cheng},

booktitle={International Conference on Learning Representations},

year={2019},

url={https://openreview.net/forum?id=H1ewdiR5tQ},

}

## Acknowledgement

> Some sections of code adapted from tkipf/gcn(https://github.com/tkipf/gcn)