1 citations · 1 across the 2 of their papers we have counts for
4 papers
DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift
Defu Cao, Yousef El-Laham, Loc Trinh +2
In electronic trading markets, limit order books (LOBs) provide information about pending buy/sell orders at various price levels for a given security. Recently, there has been a g…
An Examination of Fairness of AI Models for Deepfake Detection
Loc Trinh, Yan Liu
Recent studies have demonstrated that deep learning models can discriminate based on protected classes like race and gender. In this work, we evaluate bias present in deepfake data…
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset
Chuizheng Meng, Loc Trinh, Nan Xu +1
The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications. However, due to the nature…
Interpretable and Trustworthy Deepfake Detection via Dynamic Prototypes
Loc Trinh, Michael Tsang, Sirisha Rambhatla +1
In this paper we propose a novel human-centered approach for detecting forgery in face images, using dynamic prototypes as a form of visual explanations. Currently, most state-of-t…