193 citations · 438 across the 22 of their papers we have counts for
11 papers · 1 filter
Conditional Distribution Estimation Given Functional Covariates Using Deep Operator Networks
Bingqing Hu, Ran Zou, Bin Nan
Functional linear models are commonly used for analyzing functional data with scalar responses, particularly for modeling the conditional mean of the response given functional cova…
Nonparametric Estimation of Conditional Survival Function with Time-Varying Covariates Using DeepONet
Bingqing Hu, Bin Nan
Traditional survival models often rely on restrictive assumptions such as proportional hazards or instantaneous effects of time-varying covariates on the hazard function, which lim…
Regression for Left-Truncated and Right-Censored Data: A Semiparametric Sieve Likelihood Approach
Spencer Matthews, Bin Nan
Cohort studies of the onset of a disease often encounter left-truncation on the event time of interest in addition to right-censoring due to variable enrollment times of study part…
Debiased Lasso After Sample Splitting for Estimation and Inference in High Dimensional Generalized Linear Models
Omar Vazquez, Bin Nan
We consider random sample splitting for estimation and inference in high dimensional generalized linear models, where we first apply the lasso to select a submodel using one subsam…
De-biased lasso for stratified Cox models with application to the national kidney transplant data
Lu Xia, Bin Nan, Yi Li
The Scientific Registry of Transplant Recipients (SRTR) system has become a rich resource for understanding the complex mechanisms of graft failure after kidney transplant, a cruci…
Conditional Distribution Function Estimation Using Neural Networks for Censored and Uncensored Data
Bingqing Hu, Bin Nan
Most work in neural networks focuses on estimating the conditional mean of a continuous response variable given a set of covariates.In this article, we consider estimating the cond…