1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
Censored Flow Matching for Synthetic Time-to-Event Generation
Jianbin Tan, Xingran Chen, Kevin He +3
Generating time-to-event data is increasingly important in survival analysis, but it remains statistically challenging because event times are often censored and thus prevent flexi…
A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning
Jianhan Zhang, Jitao Wang, John D. Piette +3
Reinforcement learning (RL) seeks to optimize sequential decisions to maximize population-level benefits over time. However, when deployed in high-stakes settings such as healthcar…
Prediction-based Inference in Electronic Health Record (EHR)-linked Biobanks with Clinically Informative Outcomes
Xingran Chen, Cheng-Han Yang, Zhenke Wu +1
Electronic health record (EHR)-linked biobank data hold tremendous promise for large-scale discoveries via genome-wide association study (GWAS) on diverse phenotypic traits and bio…
Spatially Robust Inference with Predicted and Missing at Random Labels
Stephen Salerno, Zhenke Wu, Tyler McCormick
When outcome data are expensive or onerous to collect, scientists increasingly substitute predictions from machine learning and AI models for unlabeled cases, a process which has c…