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This repo covers the implementation for our paper ProMC

Zhenzhong Wang, Lulu Cao, Wanyu Lin, Min Jiang, and Kaychen Tan. "Robust Graph Meta Learning via Manifold Calibration with Proxy Subgraphs," in the Proceedings of the Thirty-Seventh Conference on Association for the Advancement of Artificial Intelligence (AAAI), Washington DC, USA, Feburary 7-14, 2023.

Dependencies

The script has been tested running under Python 3.8, with the following packages installed:

  • torch: 1.11.0
  • dgl: 0.8.2
  • scipy: 1.9.1
  • numpy: 1.21.6

In addition, CUDA 11.3 has been used in our project

Data Processing

We use the attack methods provided in DeepRobust code to process the data.

Run

   python main.py

Cite Us

@inproceedings{promcgraphnnaaai2023,
	title = {Robust Graph Meta Learning via Manifold Calibration with Proxy Subgraphs},
	author = {Wang, Zhenzhong and Cao, Lulu and Lin, Wanyu and Jiang, Min and Tan, Kaychen},
	booktitle = {Proceedings of the Thirty-Seventh Conference on Association for the Advancement of Artificial Intelligence (AAAI)},
	year = {2023}
}

About

Official code for the AAAI2023 "Robust Graph Meta Learning via Manifold Calibration with Proxy Subgraphs"

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