| CONAN: contrastive fusion networks for multi-view clustering G Ke, Z Hong, Z Zeng, Z Liu, Y Sun, Y Xie 2021 IEEE International Conference on Big Data (Big Data), 653-660, 2021 | 30 | 2021 |
| Efficient multi-view clustering networks G Ke, Z Hong, W Yu, X Zhang, Z Liu Applied Intelligence 52 (13), 14918-14934, 2022 | 20 | 2022 |
| A clustering-guided contrastive fusion for multi-view representation learning G Ke, G Chao, X Wang, C Xu, Y Zhu, Y Yu IEEE Transactions on Circuits and Systems for Video Technology, 2023 | 14 | 2023 |
| MORI-RAN: Multi-view Robust Representation Learning via Hybrid Contrastive Fusion G Ke, Y Zhu, Y Yu International Conference on Data Mining Workshops, (ICDM) 2022, 467--474, 2022 | 10 | 2022 |
| Knowledge distillation-driven semi-supervised multi-view classification X Wang, Y Wang, G Ke, Y Wang, X Hong Information Fusion 103, 102098, 2024 | 6 | 2024 |
| Disentangling multi-view representations beyond inductive bias G Ke, Y Yu, G Chao, X Wang, C Xu, S He Proceedings of the 31st ACM International Conference on Multimedia, 2582-2590, 2023 | 6 | 2023 |
| Rethinking Multi-view Representation Learning via Distilled Disentangling G Ke, B Wang, X Wang, S He Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
Xiaoli WangNanjing University of Science and Technology在 njust.edu.cn 的电子邮件经过验证
