Zhenke Wu | DeepAI

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Featured Co-authors

Min Zhang
197 publications
Rui Song
71 publications
James M. Rehg
48 publications
Chengchun Shi
31 publications
Inbal Nahum-Shani
13 publications
Bhramar Mukherjee
12 publications
Walter Dempsey
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Karthik Bharath
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Piotr Fryzlewicz
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Michael R. Elliott
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Jingshen Wang
10 publications

∙ 06/07/2023

Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations

Dietary patterns synthesize multiple related diet components, which can ...

0 Mengbing Li, et al. ∙

∙ 02/16/2023

Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies

Only about one-third of the deaths worldwide are assigned a medically-ce...

0 Toshiya Yoshida, et al. ∙

∙ 01/31/2023

A Reinforcement Learning Framework for Dynamic Mediation Analysis

Mediation analysis learns the causal effect transmitted via mediator var...

10 Lin Ge, et al. ∙

∙ 12/02/2022

Estimating Time-Varying Direct and Indirect Causal Excursion Effects with Longitudinal Binary Outcomes

Construction of just-in-time adaptive interventions, such as prompts del...

0 Jieru Shi, et al. ∙

∙ 11/08/2022

Doubly Inhomogeneous Reinforcement Learning

This paper studies reinforcement learning (RL) in doubly inhomogeneous e...

4 Liyuan Hu, et al. ∙

∙ 07/30/2022

Outcome Adaptive Propensity Score Methods for Handling Censoring and High-Dimensionality: Application to Insurance Claims

Propensity scores are commonly used to reduce the confounding bias in no...

0 Youfei Yu, et al. ∙

∙ 07/15/2022

Variance as a predictor of health outcomes: Subject-level trajectories and variability of sex hormones to predict body fat changes in peri- and post-menopausal women

Longitudinal biomarker data and cross-sectional outcomes are routinely c...

0 Irena Chen, et al. ∙

∙ 03/03/2022

Reinforcement Learning in Possibly Nonstationary Environments

We consider reinforcement learning (RL) methods in offline nonstationary...

17 Mengbing Li, et al. ∙

∙ 02/23/2022

baker: An R package for Nested Partially-Latent Class Models

This paper describes and illustrates the functionality of the baker R pa...

0 Irena B Chen, et al. ∙

∙ 01/23/2022

Probabilistic Learning of Treatment Trees in Cancer

Accurate identification of synergistic treatment combinations and their ...

0 Tsung-Hung Yao, et al. ∙

∙ 12/22/2021

Bayesian Nested Latent Class Models for Cause-of-Death Assignment using Verbal Autopsies Across Multiple Domains

Understanding cause-specific mortality rates is crucial for monitoring p...

0 Zehang Richard Li, et al. ∙

∙ 12/21/2021

Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy

Determining causes of deaths (COD) occurred outside of civil registratio...

0 Zhenke Wu, et al. ∙

∙ 11/02/2021

Dynamic statistical inference in massive datastreams

Modern technological advances have expanded the scope of applications re...

0 Jingshen Wang, et al. ∙

∙ 11/01/2021

Kernel Deformed Exponential Families for Sparse Continuous Attention

Attention mechanisms take an expectation of a data representation with r...

4 Alexander Moreno, et al. ∙

∙ 02/02/2021

Assessing Time-Varying Causal Effect Moderation in the Presence of Cluster-Level Treatment Effect Heterogeneity

Micro-randomized trial (MRT) is a sequential randomized experimental des...

0 Jieru Shi, et al. ∙

∙ 03/28/2020

A Hierarchical Integrative Group LASSO (HiGLASSO) Framework for Analyzing Environmental Mixtures

Environmental health studies are increasingly measuring multiple polluta...

0 Jonathan Boss, et al. ∙

∙ 03/02/2020

A Functional EM Algorithm for Panel Count Data with Missing Counts

Panel count data is recurrent events data where counts of events are obs...

0 Alexander Moreno, et al. ∙

∙ 02/19/2020

Weakly-supervised Multi-output Regression via Correlated Gaussian Processes

Multi-output regression seeks to infer multiple latent functions using d...

0 Seokhyun Chung, et al. ∙

∙ 06/20/2019

Regression Analysis of Dependent Binary Data for Estimating Disease Etiology from Case-Control Studies

In large-scale disease etiology studies, epidemiologists often need to u...

0 Zhenke Wu, et al. ∙

∙ 08/24/2018

A Bayesian Approach to Restricted Latent Class Models for Scientifically-Structured Clustering of Multivariate Binary Outcomes

In this paper, we propose a general framework for combining evidence of ...

0 Zhenke Wu, et al. ∙