GA-GWNN: Generalized Adaptive Graph Wavelet Neural Network

This is a repository of the paper titled: "GA-GWNN: Generalized Adaptive Graph Wavelet Neural Network".

Required Packages

• pytorch 1.12.0
• numpy 1.23.4
• torch-geometric 1.7.2
• tqdm 4.64.1
• scipy 1.9.3
• seaborn 0.12.0
• scikit-learn 1.1.3
• ogb 1.3.5

All the requirements are given inside the "requirements.txt" file.

Datasets

You can download all the datasets utilized in this paper form the Pei et. al. 2018, "Geom-GCN: Geometric Graph Convolutional Networks". Additionally, we also provide the pre-processed dataset in GoogleDrive

Code Structure

The folder "homophilic graphs" is the code for the for standard citation networks (Cora, Citeseer, PubMed); and the folder "heterophilic graphs" is the code for the results in all the heterophilic datasets. Finally "large graphs" contain code for the large scale graphs.

Environment Setup

You will require pytroch gpu version 1.12.0 from pytorch (https://pytorch.org/get-started/previous-versions/).

conda install pytorch==1.12.0 torchvision==0.13.0 torchaudio==0.12.0 cudatoolkit=11.3 -c pytorch

Then run the requirements.txt file.

pip install -r requirements.txt