Edge-Variational Graph Neural Networks: Harnessing Weak Ties for Enhanced Default Risk Prediction.
Feng Zhang|Jianfeng Chi|Rui Ma|Gang Chen|Rongqi Chen
| Anthology ID: | DBLP:conf/cikm/ZhangCMCC25 |
|---|---|
| Volume: | Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025 |
| Year: | 2025 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 6242-6249 |
| URL: | https://doi.org/10.1145/3746252.3761498 |
| DOI: | https://doi.org/10.1145/3746252.3761498 |
| DBLP: | conf/cikm/ZhangCMCC25 |
| BibTeX: |
@inproceedings{zhang-2025-edgevariational,
author = {Feng Zhang and
Jianfeng Chi and
Rui Ma and
Gang Chen and
Rongqi Chen},
editor = {Meeyoung Cha and
Carl Yang and
Senjuti Basu Roy and
Chanyoung Park and
Zhenhui Jessie Li and
Noseong Park and
Carl Yang and
Senjuti Basu Roy and
Zhenhui Jessie Li and
Jaap Kamps and
Kijung Shin and
Bryan Hooi and
Lifang He},
title = {{Edge-Variational Graph Neural Networks: Harnessing Weak Ties for Enhanced Default Risk Prediction}},
booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}},
pages = {6242--6249},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3746252.3761498},
doi = {https://doi.org/10.1145/3746252.3761498}
}