Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network-Reference-Cited by-同舟云学术

Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network

Published:2023-04-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2023
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Author:

Bi Wendong¹^ORCID,Xu Bingbing²^ORCID,Sun Xiaoqian²^ORCID,Xu Li²^ORCID,Shen Huawei²^ORCID,Cheng Xueqi²^ORCID

Affiliation:

1. Institute of Computing Technology, University of Chinese Academy of Sciences, China

2. Institute of Computing Technology, Chinese Academy of Sciences, China

Funder

Beijing Nova Program

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583287

Reference85 articles.

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3. Wendong Bi , Lun Du , Qiang Fu , Yanlin Wang , Shi Han , and Dongmei Zhang . 2022. Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach. arXiv preprint arXiv:2209.08264 ( 2022 ). Wendong Bi, Lun Du, Qiang Fu, Yanlin Wang, Shi Han, and Dongmei Zhang. 2022. Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach. arXiv preprint arXiv:2209.08264 (2022).

4. Wendong Bi , Lun Du , Qiang Fu , Yanlin Wang , Shi Han , and Dongmei Zhang . 2022. MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution. arXiv preprint arXiv:2208.07012 ( 2022 ). Wendong Bi, Lun Du, Qiang Fu, Yanlin Wang, Shi Han, and Dongmei Zhang. 2022. MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution. arXiv preprint arXiv:2208.07012 (2022).

5. Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks

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