Structure enhanced prototypical alignment for unsupervised cross-domain node classification

This is the source code of Neural Networks-2024 paper "Structure enhanced prototypical alignment for unsupervised cross-domain node classification" (SEPA).

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 SEPA framework, please consider citing the following paper:

@article{liu2024structure,
  title={Structure enhanced prototypical alignment for unsupervised cross-domain node classification},
  author={Liu, Meihan and Zhang, Zhen and Ma, Ning and Gu, Ming and Wang, Haishuai and Zhou, Sheng and Bu, Jiajun},
  journal={Neural Networks},
  volume={177},
  pages={106396},
  year={2024},
  publisher={Elsevier}
}