| Deep active learning models for imbalanced image classification Q Jin, M Yuan, H Wang, M Wang, Z Song Knowledge-Based Systems 257, 109817, 2022 | 41 | 2022 |
| One-shot active learning for image segmentation via contrastive learning and diversity-based sampling Q Jin, M Yuan, Q Qiao, Z Song Knowledge-Based Systems 241, 108278, 2022 | 40 | 2022 |
| Cold-start active learning for image classification Q Jin, M Yuan, S Li, H Wang, M Wang, Z Song Information sciences 616, 16-36, 2022 | 35 | 2022 |
| PointMBF: A Multi-scale Bidirectional Fusion Network for Unsupervised RGB-D Point Cloud Registration M Yuan, K Fu, Z Li, Y Meng, M Wang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 19 | 2023 |
| Pointclm: A contrastive learning-based framework for multi-instance point cloud registration M Yuan, Z Li, Q Jin, X Chen, M Wang European Conference on Computer Vision, 595-611, 2022 | 17 | 2022 |
| Boosting 3D Point Cloud Registration by Transferring Multi-modality Knowledge M Yuan, X Huang, K Fu, Z Li, M Wang 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023 | 14 | 2023 |
| ProteinMAE: masked autoencoder for protein surface self-supervised learning M Yuan, A Shen, K Fu, J Guan, Y Ma, Q Qiao, M Wang Bioinformatics 39 (12), btad724, 2023 | 11 | 2023 |
| Boosting point-bert by multi-choice tokens K Fu, M Yuan, S Liu, M Wang IEEE Transactions on Circuits and Systems for Video Technology 34 (1), 438-447, 2023 | 9 | 2023 |
| Decoupled deep hough voting for point cloud registration M Yuan, K Fu, Z Li, M Wang Frontiers of Computer Science 18 (2), 182703, 2024 | 6 | 2024 |
| Deep graph matching based dense correspondence learning between non-rigid point clouds J Luo, M Yuan, K Fu, M Wang, C Zhang IEEE Robotics and Automation Letters 7 (3), 5842-5849, 2022 | 6 | 2022 |
| Density-based one-shot active learning for image segmentation Q Jin, S Li, X Du, M Yuan, M Wang, Z Song Engineering Applications of Artificial Intelligence 126, 106805, 2023 | 4 | 2023 |
| PGBind: pocket-guided explicit attention learning for protein–ligand docking A Shen, M Yuan, Y Ma, J Du, M Wang Briefings in Bioinformatics 25 (5), bbae455, 2024 | 3 | 2024 |
| Complementary multi-modality molecular self-supervised learning via non-overlapping masking for property prediction A Shen, M Yuan, Y Ma, J Du, M Wang Briefings in Bioinformatics 25 (4), bbae256, 2024 | 3 | 2024 |
| Robust point cloud registration via random network co-ensemble M Yuan, K Fu, Z Li, Y Meng, A Shen, M Wang IEEE Transactions on Circuits and Systems for Video Technology 34 (7), 5742-5752, 2024 | 3 | 2024 |
| Point-MCBERT: A multi-choice self-supervised framework for point cloud pre-training K Fu, M Yuan, M Wang arXiv preprint arXiv:2207.13226, 2022 | 3 | 2022 |
| Ss-pro: A simplified siamese contrastive learning approach for protein surface representation A Shen, M Yuan, Y Ma, M Wang Frontiers of Computer Science 18 (5), 185910, 2024 | 2 | 2024 |
| SeLa-MIL: Developing an instance-level classifier via weakly-supervised self-training for whole slide image classification Y Ma, M Yuan, A Shen, X Luo, B An, X Chen, M Wang Computer Methods and Programs in Biomedicine, 108614, 2025 | | 2025 |
| PPDock: Pocket Prediction-Based Protein–Ligand Blind Docking J Du, M Yuan, A Shen, M Wang Journal of Chemical Information and Modeling, 2025 | | 2025 |
| ProteinF3S: boosting enzyme function prediction by fusing protein sequence, structure, and surface M Yuan, A Shen, Y Ma, J Du, B An, M Wang Briefings in Bioinformatics 26 (1), bbae695, 2025 | | 2025 |
| Exploring Self-Supervised Learning for 3D Point Cloud Registration M Yuan, Q Huang, A Shen, X Huang, M Wang IEEE Robotics and Automation Letters, 2024 | | 2024 |