| MMatch: Semi-supervised discriminative representation learning for multi-view classification X Wang, L Fu, Y Zhang, Y Wang, Z Li IEEE Transactions on Circuits and Systems for Video Technology 32 (9), 6425-6436, 2022 | 23 | 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 | 15 | 2023 |
| GRNet: Graph-based remodeling network for multi-view semi-supervised classification X Wang, Z Zhu, Y Song, H Fu Pattern Recognition Letters 151, 95-102, 2021 | 8 | 2021 |
| 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 | 7 | 2023 |
| 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 |
| 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 | 2 | 2024 |
| Trusted semi-supervised multi-view classification with contrastive learning X Wang, Y Wang, Y Wang, A Huang, J Liu IEEE Transactions on Multimedia, 2024 | 1 | 2024 |
Guanzhou KePh. D. candidate, Beijing Jiaotong University在 bjtu.edu.cn 的电子邮件经过验证
