FGWMixup: Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications

This is the code for the paper: Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications, published in NeurIPS'23.

Paper link 🔗:

arXiv version: https://arxiv.org/abs/2306.15963

OpenReview version: https://openreview.net/forum?id=uqkUguNu40&noteId=0qcp06CFB6

Thanks for your interest in our work! If our work helps, please don't forget to cite our paper!

File Structure

• ./src/: source codes

  gmixup_dgl.py: Main python file to run FGWMixup

  gromov_mixup.py: Conducting mixup of two samples

  FGW_barycenter.py: Calculating FGW barycenter and its accelerated version

  models_dgl.py: GNN architectures

  utils_dgl.py: Some utilities

• run_gmixup.sh: sh command to run FGWMixup

Requirements

Suggested Enviornments:

• Python 3.9
• PyTorch 1.11.0
• DGL 1.0.2
• POT 0.8.2