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05/30/2023
Testing for the Markov Property in Time Series via Deep Conditional Generative Learning
The Markov property is widely imposed in analysis of time series data. C...
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05/25/2023
High-dimensional Response Growth Curve Modeling for Longitudinal Neuroimaging Analysis
There is increasing interest in modeling high-dimensional longitudinal o...
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05/17/2023
Sequential Best-Arm Identification with Application to Brain-Computer Interface
A brain-computer interface (BCI) is a technology that enables direct com...
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10/26/2022
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach
In this article, we propose a novel pessimism-based Bayesian learning me...
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06/23/2022
Sliced Inverse Regression in Metric Spaces
In this article, we propose a general nonlinear sufficient dimension red...
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01/25/2022
NAPA: Neighborhood-Assisted and Posterior-Adjusted Two-sample Inference
Two-sample multiple testing problems of sparse spatial data are frequent...
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10/24/2021
Post-Regularization Confidence Bands for Ordinary Differential Equations
Ordinary differential equation (ODE) is an important tool to study the d...
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06/02/2021
Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning
In this article, we propose a new hypothesis testing method for directed...
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05/25/2021
Kernel Knockoffs Selection for Nonparametric Additive Models
Thanks to its fine balance between model flexibility and interpretabilit...
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05/04/2021
Nonparametric Trace Regression in High Dimensions via Sign Series Representation
Learning of matrix-valued data has recently surged in a range of scienti...
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03/29/2021
Multimodal Data Integration via Mediation Analysis with High-Dimensional Exposures and Mediators
Motivated by an imaging proteomics study for Alzheimer's disease (AD), i...
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03/12/2021
Orthogonal Statistical Inference for Multimodal Data Analysis
Multimodal imaging has transformed neuroscience research. While it prese...
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09/17/2020
Statistical Inference for High-Dimensional Vector Autoregression with Measurement Error
High-dimensional vector autoregression with measurement error is frequen...
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08/09/2020
Generalized Liquid Association Analysis for Multimodal Data Integration
Multimodal data are now prevailing in scientific research. A central que...
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08/07/2020
Kernel Ordinary Differential Equations
Ordinary differential equations (ODE) are widely used in modeling biolog...
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06/17/2020
Image-on-Scalar Regression via Deep Neural Networks
A research topic of central interest in neuroimaging analysis is to stud...
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06/03/2020
Double Generative Adversarial Networks for Conditional Independence Testing
In this article, we consider the problem of high-dimensional conditional...
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05/10/2020
Testing Mediation Effects Using Logic of Boolean Matrices
Mediation analysis is becoming an increasingly important tool in scienti...
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02/22/2020
Partially Observed Dynamic Tensor Response Regression
In modern data science, dynamic tensor data is prevailing in numerous ap...
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01/03/2020
Multivariate Temporal Point Process Regression
Point process modeling is gaining increasing attention, as point process...
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11/11/2019
Integrative Factor Regression and Its Inference for Multimodal Data Analysis
Multimodal data, where different types of data are collected from the sa...
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08/28/2019
Multimodal Neuroimaging Data Integration and Pathway Analysis
With fast advancements in technologies, the collection of multiple types...
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08/21/2019
Paired Test of Matrix Graphs and Brain Connectivity Analysis
Inferring brain connectivity network and quantifying the significance of...
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08/11/2019
Hypothesis Testing for Network Data with Power Enhancement
Comparing two population means of network data is of paramount importanc...
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06/11/2019
Quantifying Intrinsic Uncertainty in Classification via Deep Dirichlet Mixture Networks
With the widespread success of deep neural networks in science and techn...
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11/13/2018
Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and its Statistical Optimality
We consider the problem of decomposition of multiway tensor with binary ...
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10/07/2018
Network Response Regression for Modeling Population of Networks with Covariates
Multiple-network data are fast emerging in recent years, where a separat...
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06/11/2018
Mixed-Effect Time-Varying Network Model and Application in Brain Connectivity Analysis
Time-varying networks are fast emerging in a wide range of scientific an...
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08/24/2017
Dynamic Tensor Clustering
Dynamic tensor data are becoming prevalent in numerous applications. Exi...
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09/15/2016
