2024/4 The IVGD is included in our recently published Python package GraphSL.

IVGD: Invertible Validity-aware Graph Diffusion

This is an implementation of Invertible Validity-aware Graph Diffusion for the source localization problem, as described in our paper:

Junxiang Wang, Junji Jiang, and Liang Zhao. An Invertible Graph Diffusion Neural Network for Source Localization. (WWW 2022)

Feel free to Email Junxiang Wang (junxiang.wang@alumni.emory.edu) if you have any questions.

Requirement

scipy==1.5.0

torch==1.6.0

ipdb==0.13.4

numpy==1.18.5

scikit_learn==0.23.2

Implementation

python pretrain.py # train the graph diffusion model.

python main.py # train the source localization model, which is the inverse of the graph diffusion model.

Citation

Please cite our paper if you use the code in your own work.

@inproceedings{IVGD_www22,

title={An Invertible Graph Diffusion Neural Network for Source Localization},

author={Junxiang Wang, Junji Jiang, and Liang Zhao},

booktitle={Proceedings of the 31th International World Wide Web Conference (WWW 2022)},

year={2022}

}