| A hyperbolic-to-hyperbolic graph convolutional network J Dai, Y Wu, Z Gao, Y Jia Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 92 | 2021 |
| Curvature generation in curved spaces for few-shot learning Z Gao, Y Wu, Y Jia, M Harandi Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 69 | 2021 |
| Deep convolutional network with locality and sparsity constraints for texture classification X Bu, Y Wu, Z Gao, Y Jia Pattern Recognition 91, 34-46, 2019 | 64 | 2019 |
| Meta-causal learning for single domain generalization J Chen, Z Gao, X Wu, J Luo Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 47 | 2023 |
| A robust distance measure for similarity-based classification on the SPD manifold Z Gao, Y Wu, M Harandi, Y Jia IEEE transactions on neural networks and learning systems 31 (9), 3230-3244, 2019 | 44 | 2019 |
| Revisiting bilinear pooling: A coding perspective Z Gao, Y Wu, X Zhang, J Dai, Y Jia, M Harandi Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3954-3961, 2020 | 41 | 2020 |
| VideoAgent: A Memory-Augmented Multimodal Agent for Video Understanding Y Fan, X Ma, R Wu, Y Du, J Li, Z Gao, Q Li European Conference on Computer Vision, 75-92, 2024 | 39 | 2024 |
| Learning a robust representation via a deep network on symmetric positive definite manifolds Z Gao, Y Wu, X Bu, T Yu, J Yuan, Y Jia Pattern Recognition 92, 1-12, 2019 | 39 | 2019 |
| Learning to optimize on SPD manifolds Z Gao, Y Wu, Y Jia, M Harandi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 26 | 2020 |
| Clova: A closed-loop visual assistant with tool usage and update Z Gao, Y Du, X Zhang, X Ma, W Han, SC Zhu, Q Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 22 | 2024 |
| Curvature-adaptive meta-learning for fast adaptation to manifold data Z Gao, Y Wu, M Harandi, Y Jia IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 1545-1562, 2022 | 14 | 2022 |
| Hyperbolic feature augmentation via distribution estimation and infinite sampling on manifolds Z Gao, Y Wu, Y Jia, M Harandi Advances in neural information processing systems 35, 34421-34435, 2022 | 11 | 2022 |
| Learning to optimize on Riemannian manifolds Z Gao, Y Wu, X Fan, M Harandi, Y Jia IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (5), 5935-5952, 2022 | 11 | 2022 |
| Exploring data geometry for continual learning Z Gao, C Xu, F Li, Y Jia, M Harandi, Y Wu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 9 | 2023 |
| Fire: A dataset for feedback integration and refinement evaluation of multimodal models P Li, Z Gao, B Zhang, T Yuan, Y Wu, M Harandi, Y Jia, SC Zhu, Q Li arXiv preprint arXiv:2407.11522, 2024 | 4 | 2024 |
| Learning a gradient-free Riemannian optimizer on tangent spaces X Fan, Z Gao, Y Wu, Y Jia, M Harandi Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 7377-7384, 2021 | 4 | 2021 |
| Efficient Riemannian meta-optimization by implicit differentiation X Fan, Y Wu, Z Gao, Y Jia, M Harandi Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 3733-3740, 2022 | 3 | 2022 |
| Infinite-dimensional feature aggregation via a factorized bilinear model J Dai, Y Wu, Z Gao, Y Jia Pattern Recognition 124, 108397, 2022 | 1 | 2022 |
| Large-scale riemannian meta-optimization via subspace adaptation P Yu, Y Wu, Z Gao, X Fan, Y Jia Computer Vision and Image Understanding, 104306, 2025 | | 2025 |
| Multi-modal Agent Tuning: Building a VLM-Driven Agent for Efficient Tool Usage Z Gao, B Zhang, P Li, X Ma, T Yuan, Y Fan, Y Wu, Y Jia, SC Zhu, Q Li arXiv preprint arXiv:2412.15606, 2024 | | 2024 |
yunde jiaProfessor of Computer Science, Beijing Institute of TechnologyПідтверджена електронна адреса в bit.edu.cn