Bayesian Compressed Regression - Rajarshi Guhaniyogi; David B. Dunson (CoRR, 2013)

Bayesian Conditional Density Filtering for Big Data. - Rajarshi Guhaniyogi; Shaan Qamar; David B. Dunson (CoRR, 2014)

Compressed Gaussian Process for Manifold Regression. - Rajarshi Guhaniyogi; David B. Dunson (J. Mach. Learn. Res., 2016)

Bayesian Tensor Regression. - Rajarshi Guhaniyogi; Shaan Qamar; David B. Dunson (J. Mach. Learn. Res., 2017)

Convergence rate of Bayesian supervised tensor modeling with multiway shrinkage priors. - Rajarshi Guhaniyogi (J. Multivar. Anal., 2017)

Meta-Kriging: Scalable Bayesian Modeling and Inference for Massive Spatial Datasets. - Rajarshi Guhaniyogi; Sudipto Banerjee (Technometrics, 2018)

High Dimensional Bayesian Regularization in Regressions Involving Symmetric Tensors. - Rajarshi Guhaniyogi (IPMU (3), 2020)

Bayesian Generalized Sparse Symmetric Tensor-on-Vector Regression. - Sharmistha Guha; Rajarshi Guhaniyogi (Technometrics, 2021)

Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior. - Rajarshi Guhaniyogi; Cheng Li; Terrance D. Savitsky; Sanvesh Srivastava (J. Mach. Learn. Res., 2022)

Bayesian Dynamic Feature Partitioning in High-Dimensional Regression With Big Data. - Rene Gutierrez; Rajarshi Guhaniyogi (Technometrics, 2022)

InVA: Integrative Variational Autoencoder for Harmonization of Multi-modal Neuroimaging Data. - Bowen Lei; Rajarshi Guhaniyogi; Krishnendu Chandra; Aaron Scheffler; Bani K. Mallick (CoRR, 2024)

Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data. - Sharmistha Guha; Rajarshi Guhaniyogi (Technometrics, 2024)

Bayesian Data Sketching for Varying Coefficient Regression Models. - Rajarshi Guhaniyogi; Laura Baracaldo; Sudipto Banerjee (CoRR, 2025)