activity
20232025
most citedKernel meets sieve: transformed hazards models with sparse longitudinal covariates

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2025

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…

stat.ML2025

Optimal Transport Learning: Balancing Value Optimization and Fairness in Individualized Treatment Rules

Wenhai Cui, Xiaoting Ji, Wen Su +2

Individualized treatment rules (ITRs) have gained significant attention due to their wide-ranging applications in fields such as precision medicine, ridesharing, and advertising re…

stat.ME2025

Demographic Parity-aware Individualized Treatment Rules

Wenhai Cui, Wen Su, Xiaodong Yan +2

There has been growing interest in developing optimal individualized treatment rules (ITRs) in various fields, such as precision medicine, business decision-making, and social welf…

stat.ME2024

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…

stat.ME20231 cited

Kernel meets sieve: transformed hazards models with sparse longitudinal covariates

Dayu Sun, Zhuowei Sun, Xingqiu Zhao +1

We study the transformed hazards model with time-dependent covariates observed intermittently for the censored outcome. Existing work assumes the availability of the whole trajecto…