Yanxun Xu

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Johns Hopkins University

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Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation

This paper presents a computational framework that generates ensemble pr...
05/20/2021 ∙ by Xiao Sun, et al. ∙ 0 ∙ share

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Personalized Dynamic Treatment Regimes in Continuous Time: A Bayesian Joint Model for Optimizing Clinical Decisions with Timing

Accurate models of clinical actions and their impacts on disease progres...
07/08/2020 ∙ by William Hua, et al. ∙ 0 ∙ share

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BAGEL: A Bayesian Graphical Model for Inferring Drug Effect Longitudinally on Depression in People with HIV

Access and adherence to antiretroviral therapy (ART) has transformed the...
07/03/2020 ∙ by Yuliang Li, et al. ∙ 0 ∙ share

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A Bayesian Nonparametric Approach for Inferring Drug Combination Effects on Mental Health in People with HIV

Although combination antiretroviral therapy (ART) is highly effective in...
04/11/2020 ∙ by Wei Jin, et al. ∙ 0 ∙ share

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Efficient Estimation for Random Dot Product Graphs via a One-step Procedure

We propose a one-step procedure to efficiently estimate the latent posit...
10/10/2019 ∙ by Fangzheng Xie, et al. ∙ 0 ∙ share

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Optimal Bayesian Estimation for Random Dot Product Graphs

We propose a Bayesian approach, called the posterior spectral embedding,...
04/26/2019 ∙ by Fangzheng Xie, et al. ∙ 0 ∙ share

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A Bayesian Nonparametric Approach for Evaluating the Effect of Treatment in Randomized Trials with Semi-Competing Risks

We develop a Bayesian nonparametric (BNP) approach to evaluate the effec...
03/20/2019 ∙ by Yanxun Xu, et al. ∙ 0 ∙ share

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BAREB: A Bayesian repulsive biclustering model for periodontal data

Preventing periodontal diseases (PD) and maintaining the structure and f...
02/15/2019 ∙ by Yuliang Li, et al. ∙ 0 ∙ share

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ASIED: A Bayesian Adaptive Subgroup-Identification Enrichment Design

Developing targeted therapies based on patients' baseline characteristic...
10/04/2018 ∙ by Yanxun Xu, et al. ∙ 0 ∙ share

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Bayesian Estimation of Sparse Spiked Covariance Matrices in High Dimensions

We propose a Bayesian methodology for estimating spiked covariance matri...
08/22/2018 ∙ by Fangzheng Xie, et al. ∙ 0 ∙ share

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Bayesian Projected Calibration of Computer Models

We develop a Bayesian approach called Bayesian projected calibration to ...
03/03/2018 ∙ by Fangzheng Xie, et al. ∙ 0 ∙ share

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A Theoretical Framework for Bayesian Nonparametric Regression: Orthonormal Random Series and Rates of Contraction

We develop a unifying framework for Bayesian nonparametric regression to...
12/15/2017 ∙ by Fangzheng Xie, et al. ∙ 0 ∙ share

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Nonseparable Gaussian Stochastic Process: A Unified View and Computational Strategy

Gaussian stochastic process (GaSP) has been widely used as a prior over ...
11/30/2017 ∙ by Mengyang Gu, et al. ∙ 0 ∙ share

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Adaptive Bayesian nonparametric regression using kernel mixture of polynomials with application to partial linear model

We propose a kernel mixture of polynomials prior for Bayesian nonparamet...
10/22/2017 ∙ by Fangzheng Xie, et al. ∙ 0 ∙ share

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A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves

We study the problem of estimating the continuous response over time to ...
08/18/2016 ∙ by Yanbo Xu, et al. ∙ 0 ∙ share

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