Skip to content

Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification

Notifications You must be signed in to change notification settings

flyingdoog/PTDNet

Repository files navigation

PTDNet

This is a Tensorflow implementation of paper: Learning to Drop: Robust Graph Neural Network via Topological Denoising

https://arxiv.org/abs/2011.07057

WSDM'21

Unofficial Implementation Robust Graph Representation Learning via Neural Sparsification

ICML 20

Since the previous version is not easy to use, I've updated the code from Tensorflow 1.0 to Tensorflow 2.0. Currently, I only provide sample implementation for reference. Hyper-parameters for different datasets need tune.

Requirements

  • Python 3.8.6
  • tensorflow 2.3.1
  • networkx

References

@inproceedings{luo2021learning,
  title={Learning to Drop: Robust Graph Neural Network via Topological Denoising},
  author={Luo, Dongsheng and Cheng, Wei and Yu, Wenchao and Zong, Bo and Ni, Jingchao and Chen, Haifeng, and Zhang, Xiang},
  booktitle={Proceedings of the 14th ACM International Conference on Web Search and Data Mining},
  year={2021},
  organization={ACM}
}

About

Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages