[WWW 2022] Curvature Graph Generative Adversarial Networks (CurvGAN)

This repository is the implementation of CurvGAN in PyTorch.

Environment

python==3.7.1
pytorch==1.8.0
networkx==2.5.1
scikit-learn==0.24.2
pandas==1.2.4
GraphRicciCurvature==0.5.3
numpy==1.20.3

and their dependencies.

Usage

1. Setup

• Clone this repo
• Create a virtual environment using conda or virtualenv.

  conda env create -f environment.yml
  virtualenv -p [PATH to python3.6 binary] curvgan
  

• Enter the virtual environment and run pip install -r requirements.txt.

2. Usage

• Create a config file in config/
• Run python curvgan.py [--config config_filename] to train our model, with setting custom parameters.
  • An example, for link prediction (LP) task on Cora dataset: python curvgan.py --config cora-lp-best.yaml

Thanks

Some of the code was forked from the following repositories:

• HazyResearch/HGCN;
• emilemathieu/pvae;

We deeply thanks for their contributions to the open-source community.