| Non-parametric message importance measure: Storage code design and transmission planning for big data S Liu, R She, P Fan, KB Letaief IEEE Transactions on Communications 66 (11), 5181-5196, 2018 | 21 | 2018 |
| Focusing on a probability element: Parameter selection of message importance measure in big data R She, S Liu, Y Dong, P Fan 2017 IEEE International Conference on Communications (ICC), 1-6, 2017 | 19 | 2017 |
| Amplifying inter-message distance: On information divergence measures in big data R She, S Liu, P Fan IEEE Access 5, 24105-24119, 2017 | 14 | 2017 |
| Graph neural convection-diffusion with heterophily K Zhao, Q Kang, Y Song, R She, S Wang, WP Tay International Joint Conference on Artificial Intelligence (IJCAI), 2023 | 13 | 2023 |
| RobustLoc: Robust camera pose regression in challenging driving environments S Wang, Q Kang, R She, WP Tay, A Hartmannsgruber, DN Navarro Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 6209-6216, 2023 | 12 | 2023 |
| Importance of small probability events in big data: Information measures, applications, and challenges R She, S Liu, S Wan, K Xiong, P Fan IEEE Access 7, 100363-100382, 2019 | 11 | 2019 |
| Differential message importance measure: A new approach to the required sampling number in big data structure characterization S Liu, R She, P Fan IEEE Access 6, 42851-42867, 2018 | 9 | 2018 |
| Recognizing information feature variation: Message importance transfer measure and its applications in big data R She, S Liu, P Fan Entropy 20 (6), 401, 2018 | 9 | 2018 |
| HypLiLoc: Towards effective LiDAR pose regression with hyperbolic fusion S Wang, Q Kang, R She, W Wang, K Zhao, Y Song, WP Tay Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
| Adversarial robustness in graph neural networks: A Hamiltonian approach K Zhao, Q Kang, Y Song, R She, S Wang, WP Tay Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| Interpretable generative adversarial networks with exponential function R She, P Fan, XY Liu, X Wang IEEE Transactions on Signal Processing 69, 3854-3867, 2021 | 7 | 2021 |
| Robustmat: Neural diffusion for street landmark patch matching under challenging environments R She, Q Kang, S Wang, YR Yáng, K Zhao, Y Song, WP Tay IEEE Transactions on Image Processing, 2023 | 6 | 2023 |
| From MIM-based GAN to anomaly detection: Event probability influence on generative adversarial networks R She, P Fan IEEE Internet of Things Journal 9 (19), 18589-18606, 2022 | 6* | 2022 |
| Attention to the variation of probabilistic events: Information processing with message importance measure R She, S Liu, P Fan Entropy 21 (5), 439, 2019 | 6 | 2019 |
| Image patch-matching with graph-based learning in street scenes R She, Q Kang, S Wang, WP Tay, YL Guan, DN Navarro, ... IEEE Transactions on Image Processing, 2023 | 5 | 2023 |
| Matching users’ preference under target revenue constraints in data recommendation systems S Liu, Y Dong, P Fan, R She, S Wan Entropy 21 (2), 205, 2019 | 5 | 2019 |
| Non-parametric message important measure: Compressed storage design for big data in wireless communication systems S Liu, R She, P Fan, J Lu 2017 23rd Asia-Pacific Conference on Communications (APCC), 1-6, 2017 | 5 | 2017 |
| Location learning for AVs: Lidar and image landmarks fusion localization with graph neural networks Q Kang, R She, S Wang, WP Tay, DN Navarro, A Hartmannsgruber 2022 IEEE 25th International Conference on Intelligent Transportation …, 2022 | 4 | 2022 |
| A switch to the concern of user: Importance coefficient in utility distribution and message importance measure S Liu, R She, S Wan, P Fan, Y Dong 2018 14th International Wireless Communications & Mobile Computing …, 2018 | 4 | 2018 |
| Storage space allocation strategy for digital data with message importance S Liu, R She, Z Zhu, P Fan Entropy 22 (5), 591, 2020 | 3 | 2020 |
Pingyi FanProfessor of Electronic Engineering, Tsinghua UniversityПотвърден имейл адрес: tsinghua.edu.cn
