| Few-shot learning via embedding adaptation with set-to-set functions HJ Ye, H Hu, DC Zhan, F Sha Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 979* | 2020 |
| Foster: Feature boosting and compression for class-incremental learning FY Wang, DW Zhou, HJ Ye, DC Zhan European conference on computer vision, 398-414, 2022 | 317 | 2022 |
| Class-incremental learning: A survey DW Zhou, QW Wang, ZH Qi, HJ Ye, DC Zhan, Z Liu IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 272* | 2024 |
| Learning placeholders for open-set recognition DW Zhou, HJ Ye, DC Zhan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 270 | 2021 |
| Forward compatible few-shot class-incremental learning DW Zhou, FY Wang, HJ Ye, L Ma, S Pu, DC Zhan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 249 | 2022 |
| A model or 603 exemplars: Towards memory-efficient class-incremental learning DW Zhou, QW Wang, HJ Ye, DC Zhan arXiv preprint arXiv:2205.13218, 2022 | 181 | 2022 |
| Few-shot class-incremental learning by sampling multi-phase tasks DW Zhou, HJ Ye, L Ma, D Xie, S Pu, DC Zhan IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (11 …, 2022 | 129 | 2022 |
| Identifying and compensating for feature deviation in imbalanced deep learning HJ Ye, HY Chen, DC Zhan, WL Chao arXiv preprint arXiv:2001.01385, 2020 | 108 | 2020 |
| The capacity and robustness trade-off: Revisiting the channel independent strategy for multivariate time series forecasting L Han, HJ Ye, DC Zhan IEEE Transactions on Knowledge and Data Engineering, 2024 | 92 | 2024 |
| Pycil: A python toolbox for class-incremental learning DW Zhou, FY Wang, HJ Ye, DC Zhan Science China Information Sciences 66 (9), 197101, 2023 | 85 | 2023 |
| Learning adaptive classifiers synthesis for generalized few-shot learning HJ Ye, H Hu, DC Zhan International Journal of Computer Vision 129 (6), 1930-1953, 2021 | 84 | 2021 |
| Decaug: Out-of-distribution generalization via decomposed feature representation and semantic augmentation H Bai, R Sun, L Hong, F Zhou, N Ye, HJ Ye, SHG Chan, Z Li Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 6705-6713, 2021 | 81 | 2021 |
| Gen-l-video: Multi-text to long video generation via temporal co-denoising FY Wang, W Chen, G Song, HJ Ye, Y Liu, H Li arXiv preprint arXiv:2305.18264, 2023 | 74 | 2023 |
| Co-transport for class-incremental learning DW Zhou, HJ Ye, DC Zhan Proceedings of the 29th ACM International Conference on Multimedia, 1645-1654, 2021 | 71 | 2021 |
| Beef: Bi-compatible class-incremental learning via energy-based expansion and fusion FY Wang, DW Zhou, L Liu, HJ Ye, Y Bian, DC Zhan, P Zhao The eleventh international conference on learning representations, 2022 | 63 | 2022 |
| Few-shot learning with a strong teacher HJ Ye, L Ming, DC Zhan, WL Chao IEEE transactions on pattern analysis and machine intelligence 46 (3), 1425-1440, 2022 | 63 | 2022 |
| How to train your MAML to excel in few-shot classification HJ Ye, WL Chao arXiv preprint arXiv:2106.16245, 2021 | 59 | 2021 |
| Continual learning with pre-trained models: A survey DW Zhou, HL Sun, J Ning, HJ Ye, DC Zhan arXiv preprint arXiv:2401.16386, 2024 | 53 | 2024 |
| What makes objects similar: A unified multi-metric learning approach HJ Ye, DC Zhan, XM Si, Y Jiang, ZH Zhou Advances in neural information processing systems 29, 2016 | 52 | 2016 |
| Few-shot class-incremental learning via training-free prototype calibration QW Wang, DW Zhou, YK Zhang, DC Zhan, HJ Ye Advances in Neural Information Processing Systems 36, 2024 | 50 | 2024 |
De-Chuan ZhanNanjing University, ChinaZweryfikowany adres z nju.edu.cn