/WARGA

The experimental implementation for the paper Wasserstein Adversarially Regularized Graph Autoencoder

Primary LanguageJupyter NotebookOtherNOASSERTION

WARGA

The experiment implementation (PyTorch) for paper Wasserstein Adversarially Regularized Graph Autoencoder.

WARGA

Requirements

  • Pytorch 1.8.1
  • Python 3.8
  • scikit-learn
  • networkx
  • munkres
  • pickle
  • scipy

Run

  • WARGA.py for WARGA-WC.
  • WARGA GP.py for WARGA-GP.
  • WARGA-GP Clustering Notebook.ipynb for WARGA-GP clustering results reproduction.
  • WARGA-GP Link Prediction Notebook.ipynb for WARGA-GP link prediction results reproduction.
  • WARGA-WC Clustering Notebook.ipynb for WARGA-WC clustering results reproduction.
  • WARGA-WC Link Prediction Notebook.ipynb for WARGA-WC link prediction results reproduction.