Can higher-order structural features improve the performance of graph neural networks for graph classification?

Xin Chen, Miao Liu, Yue Peng, Benyun Shi. Can higher-order structural features improve the performance of graph neural networks for graph classification?. In IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2022, Niagara Falls, ON, Canada, November 17-20, 2022. pages 788-795, IEEE, 2022. [doi]

@inproceedings{ChenLPS22-0,
  title = {Can higher-order structural features improve the performance of graph neural networks for graph classification?},
  author = {Xin Chen and Miao Liu and Yue Peng and Benyun Shi},
  year = {2022},
  doi = {10.1109/WI-IAT55865.2022.00130},
  url = {https://doi.org/10.1109/WI-IAT55865.2022.00130},
  researchr = {https://researchr.org/publication/ChenLPS22-0},
  cites = {0},
  citedby = {0},
  pages = {788-795},
  booktitle = {IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2022, Niagara Falls, ON, Canada, November 17-20, 2022},
  publisher = {IEEE},
  isbn = {978-1-6654-9402-1},
}