| Interpretability and fairness evaluation of deep learning models on MIMIC-IV dataset C Meng, L Trinh, N Xu, J Enouen, Y Liu Scientific Reports 12 (1), 7166, 2022 | 152 | 2022 |
| Interpretable and trustworthy deepfake detection via dynamic prototypes L Trinh, M Tsang, S Rambhatla, Y Liu Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021 | 115 | 2021 |
| A multi-scale time-series dataset with benchmark for machine learning in decarbonized energy grids X Zheng, N Xu, L Trinh, D Wu, T Huang, S Sivaranjani, Y Liu, L Xie Scientific Data 9 (1), 359, 2022 | 47* | 2022 |
| An Examination of Fairness of AI Models for Deepfake Detection L Trinh, Y Liu Proceedings of the Thirtieth International Joint Conference on Artificial …, 2021 | 39 | 2021 |
| Survival analysis using surgeon skill metrics and patient factors to predict urinary continence recovery after robot-assisted radical prostatectomy L Trinh, S Mingo, EB Vanstrum, DI Sanford, R Ma, JH Nguyen, Y Liu, ... European urology focus 8 (2), 623-630, 2022 | 36 | 2022 |
| Surgical gestures as a method to quantify surgical performance and predict patient outcomes R Ma, A Ramaswamy, J Xu, L Trinh, D Kiyasseh, TN Chu, EY Wong, ... NPJ Digital Medicine 5 (1), 187, 2022 | 33 | 2022 |
| Mimic-if: Interpretability and fairness evaluation of deep learning models on mimic-iv dataset C Meng, L Trinh, N Xu, Y Liu arXiv preprint arXiv:2102.06761, 2021 | 25 | 2021 |
| Detecting out-of-context multimodal misinformation with interpretable neural-symbolic model Y Zhang, L Trinh, D Cao, Z Cui, Y Liu arXiv preprint arXiv:2304.07633, 2023 | 19 | 2023 |
| Simulating continuous-time human mobility trajectories N Xu, L Trinh, S Rambhatla, Z Zeng, J Chen, S Assefa, Y Liu Proc. 9th Int. Conf. Learn. Represent, 1-9, 2021 | 13 | 2021 |
| DL4Burn: Burn surgical candidacy prediction using multimodal deep learning S Rambhatla, S Huang, L Trinh, M Zhang, B Long, M Dong, V Unadkat, ... AMIA Annual Symposium Proceedings 2021, 1039, 2022 | 11 | 2022 |
| Greedy layerwise training of convolutional neural networks LQ Trinh Massachusetts Institute of Technology, 2019 | 9 | 2019 |
| PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids (Dataset) X Zheng, N Xu, D Wu, L Trinh, T Huang, S Sivaranjani, Y Liu, L Xie Zenodo https://doi. org/10.5281/zenodo 5130612, 2021 | 6 | 2021 |
| A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift D Cao, Y El-Laham, L Trinh, S Vyetrenko, Y Liu NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022 | 5 | 2022 |
| Interpretable Detection of Out-of-Context Misinformation with Neural-Symbolic-Enhanced Large Multimodal Model Y Zhang, L Trinh, D Cao, Z Cui, Y Liu arXiv preprint arXiv:2304.07633, 2023 | 2 | 2023 |
| DSLOB: a synthetic limit order book dataset for benchmarking forecasting algorithms under distributional shift D Cao, Y El-Laham, L Trinh, S Vyetrenko, Y Liu arXiv preprint arXiv:2211.11513, 2022 | 2 | 2022 |
| Self-supervised Sim-to-Real Kinematics Reconstruction for Video-Based Assessment of Intraoperative Suturing Skills L Trinh, T Chu, Z Cui, A Malpani, C Yang, I Dalieh, A Hui, O Gomez, Y Liu, ... International Conference on Medical Image Computing and Computer-Assisted …, 2023 | | 2023 |
| PD01-01 ENHANCED KINEMATICS AND MULTI-MODALITY LEARNING TO IMPROVE AUTOMATION OF SUTURING SKILLS ASSESSMENT L Trinh, TN Chu, A Ghazi, JW Davis, BJ Miles, C Lau, A Malpani, Y Liu, ... The Journal of Urology 209 (Supplement 4), e62, 2023 | | 2023 |
| MP41-01 DISSECTION ASSESSMENT FOR ROBOTIC TECHNIQUE (DART) TO EVALUATE NERVE-SPARE OF ROBOT-ASSISTED RADICAL PROSTATECTOMY R Ma, A Hui, J Xu, A Desai, M Tzeng, E Cheng, L Trinh, JH Nguyen, ... The Journal of Urology 207 (Supplement 5), e718, 2022 | | 2022 |
Yan LiuProfessor, Director of Machine Learning Center@USCΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα usc.edu
