1 citations · 1 across the 8 of their papers we have counts for
9 papers
A Bayesian Vertical Federated Learning Framework for Multivariate Reduced-Rank High-Dimensional Regression
Brigham Halverson, Sharmistha Guha, Jessica Bernard +1
Federated learning (FL) has emerged as a leading privacy-preserving framework for collaborative machine learning across decentralized environments. While considerable progress has…
A Bayesian Framework for Quantifying Association Between Functional and Structural Data in Neuroimaging
Sakul Mahat, Sharmistha Guha, Jessica Bernard
Structural and functional neuroimaging modalities provide complementary windows into brain organization: structural imaging characterizes neural tissue anatomy and microstructure,…
Integrative Predictor-Dependent Learning of Network Data and Spatially Correlated Nodal Attributes for Multimodal Brain Imaging in Aging
Jose Rodriguez-Acosta, Sharmistha Guha, Jessica Bernard +2
This article introduces a predictor-dependent joint modeling framework for network data obtained from multiple subjects over a shared set of nodes with spatial co-ordinates and spa…
Integrative Learning of Dynamically Evolving Multiplex Graphs and Nodal Attributes Using Neural Network Gaussian Processes with an Application to Dynamic Terrorism Graphs
Jose Rodriguez-Acosta, Sharmistha Guha, Lekha Patel +1
Exploring the dynamic co-evolution of multiplex graphs and nodal attributes is a compelling question in criminal and terrorism networks. This article is motivated by the study of d…
Multiview Graph Fusion with Covariates
Sharmistha Guha, Jose Rodriguez-Acosta, Ivo Dinov
Joint modeling of multiview graphs with a common set of nodes between views and auxiliary predictors is an essential, yet less explored, area in statistical methodology. Traditiona…
Differentially Private Estimation of Weighted Average Treatment Effects for Binary Outcomes
Sharmistha Guha, Jerome P. Reiter
In the social and health sciences, researchers often make causal inferences using sensitive variables. These researchers, as well as the data holders themselves, may be ethically a…
High Dimensional Bayesian Network Classification with Network Global-Local Shrinkage Priors
Sharmistha Guha, Abel Rodriguez
This article proposes a novel Bayesian classification framework for networks with labeled nodes. While literature on statistical modeling of network data typically involves analysi…
Bayesian Causal Inference with Bipartite Record Linkage
Sharmistha Guha, Jerome P. Reiter, Andrea Mercatanti
In many scenarios, the observational data needed for causal inferences are spread over two data files. In particular, we consider scenarios where one file includes covariates and t…
Bayesian Regression with Undirected Network Predictors with an Application to Brain Connectome Data
Sharmistha Guha, Abel Rodriguez
This article proposes a Bayesian approach to regression with a continuous scalar response and an undirected network predictor. Undirected network predictors are often expressed in…