Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation

This is the source code of AAAI-2025 paper "Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation" (TDSS). We made modifications based on this code: https://github.com/Meihan-Liu/24AAAI-A2GNN

Requirements

This code requires the following:

• torch==1.11.0
• torch-scatter==2.0.9
• torch-sparse==0.6.13
• torch-cluster==1.6.0
• torch-geometric==2.1.0
• numpy==1.19.2
• scikit-learn==0.24.2

Dataset

Datasets used in the paper are all publicly available datasets. You can find Twitch and Citation via the links.

Cite

If you compare with, build on, or use aspects of framework, please consider citing the following paper:

@article{chen2025smoothness,
  title={Smoothness Really Matters: A Simple yet Effective Approach for Unsupervised Graph Domain Adaptation},
  author={Chen, Wei and Ye, Guo and Wang, Yakun and Zhang, Zhao and Zhang, Libang and Wang, Daxin and Zhang, Zhiqiang and Zhuang, Fuzhen},
  journal={AAAI},
  year={2025}
}