This repo provides a PyTorch implementation for the CopulaGNN models as described in the following paper:
Jiaqi Ma, Bo Chang, Xuefei Zhang, and Qiaozhu Mei. ICLR 2021.
Most dependency packages are included in environment.yml. Run conda torch_env create -f environment.yml to install the required packages.
In addition, one also needs to install PyTorch-Geometric following the official installation instructions.
The code is tested with the following PyTorch-Geometric version.
torch-scatter==2.0.5
torch-sparse==0.6.7
torch-cluster==1.5.7
torch-geometric==1.6.1
Example: python main.py --lr 0.001 --hidden_size 16 --dataset wiki-squirrel --model_type regcgcn.
@article{ma2020copulagnn,
title={CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks},
author={Ma, Jiaqi and Chang, Bo and Zhang, Xuefei and Mei, Qiaozhu},
booktitle={International Conference on Learning Representations},
year={2021}
}