Loc Trinh

According to our database, Loc Trinh authored at least 10 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Detecting Out-of-Context Multimodal Misinformation with interpretable neural-symbolic model.

Yizhou Zhang, Loc Trinh, Defu Cao, Zijun Cui, Yan Liu

CoRR, 2023

Self-supervised Sim-to-Real Kinematics Reconstruction for Video-Based Assessment of Intraoperative Suturing Skills.

Loc Trinh, Tim Chu, Zijun Cui, Anand Malpani, Cherine Yang, Istabraq Dalieh, Alvin Hui, Oscar Gomez, Yan Liu, Andrew J. Hung

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022

Surgical gestures as a method to quantify surgical performance and predict patient outcomes.

Runzhuo Ma, Ashwin Ramaswamy, Jiashu Xu, Loc Trinh, Dani Kiyasseh, Timothy N. Chu, Elyssa Y. Wong, Ryan S. Lee, Ivan Rodriguez, Gina Demeo, Aditya Desai, Maxwell X. Otiato, Sidney I. Roberts, Jessica H. Nguyen, Jasper Laca, Yan Liu, Katarina Urbanova, Christian Wagner, Animashree Anandkumar, Jim C. Hu, Andrew J. Hung

npj Digit. Medicine, 2022

DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift.

Defu Cao, Yousef El-Laham, Loc Trinh, Svitlana Vyetrenko, Yan Liu

CoRR, 2022

2021

PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids.

Xiangtian Zheng, Nan Xu, Loc Trinh, Dongqi Wu, Tong Huang, S. Sivaranjani, Yan Liu, Le Xie

CoRR, 2021

MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset.

Chuizheng Meng, Loc Trinh, Nan Xu, Yan Liu

CoRR, 2021

Interpretable and Trustworthy Deepfake Detection via Dynamic Prototypes.

Loc Trinh, Michael Tsang, Sirisha Rambhatla, Yan Liu

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

An Examination of Fairness of AI Models for Deepfake Detection.

Loc Trinh, Yan Liu

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

DL4Burn: Burn Surgical Candidacy Prediction using Multimodal Deep Learning.

Sirisha Rambhatla, Samantha Huang, Loc Trinh, Mengfei Zhang, Boyuan Long, Mingtao Dong, Vyom Unadkat, Haig Yenikomshian, Justin Gillenwater, Yan Liu

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

Interpretable Deepfake Detection via Dynamic Prototypes.

Loc Trinh, Michael Tsang, Sirisha Rambhatla, Yan Liu

CoRR, 2020