3 citations · 3 across the 9 of their papers we have counts for
9 papers
Deep Optimal Individualized Treatment Rules for Bivariate Survival Outcomes via Adaptive Prediction-Powered Learning
Kun Ren, Yifan Cui, Wen Su
In randomized trials involving multiple treatments, bivariate survival outcomes present significant analytical challenges for making decisions. This paper addresses the problem of…
Identification and Inference for Structural Accelerated Failure Time Models via Instrument Interactions
Qiushi Bu, Wen Su, Xinyu Zhang +2
We study causal inference for time-to-event outcomes under right censoring in the presence of unmeasured confounding. Focusing on structural accelerated failure time models, we dev…
Flexible semiparametric modeling with application to Causal Inference
Kun Ren, Wen Su, Li Liu +2
This paper proposes a flexible new framework for constructing Neyman-orthogonal scores in semiparametric models involving infinite-dimensional nuisance parameters. While locally es…
Learning Optimal Distributionally Robust Individualized Treatment Rules Integrating Multi-Source Data
Wenhai Cui, Wen Su, Xingqiu Zhao
Integrative analysis of multiple datasets for estimating optimal individualized treatment rules (ITRs) can enhance decision efficiency. A central challenge is posterior shift, wher…
Learning Optimal Individualized Decision Rules with Conditional Demographic Parity
Wenhai Cui, Wen Su, Donglin Zeng +1
Individualized decision rules (IDRs) have become increasingly prevalent in societal applications such as personalized marketing, healthcare, and public policy design. However, a cr…
Semiparametric Causal Inference for Right-Censored Outcomes with Many Weak Invalid Instruments
Qiushi Bu, Wen Su, Xingqiu Zhao +1
We propose a semiparametric framework for causal inference with right-censored survival outcomes and many weak invalid instruments, motivated by Mendelian randomization in biobank…
Deep Nonparametric Inference for Conditional Hazard Function
Wen Su, Kin-Yat Liu, Guosheng Yin +2
We propose a novel deep learning approach to nonparametric statistical inference for the conditional hazard function of survival time with right-censored data. We use a deep neural…
Efficient Estimation for Functional Accelerated Failure Time Model
Changyu Liu, Wen Su, Kin-Yat Liu +2
We propose a functional accelerated failure time model to characterize effects of both functional and scalar covariates on the time to event of interest, and provide regularity con…
Deep Generative Survival Analysis: Nonparametric Estimation of Conditional Survival Function
Xingyu Zhou, Wen Su, Changyu Liu +3
We propose a deep generative approach to nonparametric estimation of conditional survival and hazard functions with right-censored data. The key idea of the proposed method is to f…