Rajarshi Guhaniyogi

According to our database, Rajarshi Guhaniyogi authored at least 15 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Mapping Drivers of Greenness: Spatial Variable Selection for MODIS Vegetation Indices.

Qishi Zhan, Cheng-Han Yu, Yuchi Chen, Zhikang Dong, Rajarshi Guhaniyogi

CoRR, February, 2026

2025

Sketching in High-Dimensional Regression With Big Data Using Gaussian Scale Mixture Priors.

Rajarshi Guhaniyogi, Aaron Wolfe Scheffler

J. Mach. Learn. Res., 2025

Bayesian Data Sketching for Varying Coefficient Regression Models.

Rajarshi Guhaniyogi, Laura Baracaldo, Sudipto Banerjee

J. Mach. Learn. Res., 2025

2024

Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data.

Sharmistha Guha, Rajarshi Guhaniyogi

Technometrics, July, 2024

InVA: Integrative Variational Autoencoder for Harmonization of Multi-modal Neuroimaging Data.

Bowen Lei, Rajarshi Guhaniyogi, Krishnendu Chandra, Aaron W. Scheffler, Bani K. Mallick

CoRR, 2024

2022

Bayesian Dynamic Feature Partitioning in High-Dimensional Regression With Big Data.

Rene Gutierrez, Rajarshi Guhaniyogi

Technometrics, 2022

Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior.

Rajarshi Guhaniyogi, Cheng Li, Terrance D. Savitsky, Sanvesh Srivastava

J. Mach. Learn. Res., 2022

2021

Bayesian Generalized Sparse Symmetric Tensor-on-Vector Regression.

Sharmistha Guha, Rajarshi Guhaniyogi

Technometrics, 2021

2020

High Dimensional Bayesian Regularization in Regressions Involving Symmetric Tensors.

Rajarshi Guhaniyogi

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

2018

Meta-Kriging: Scalable Bayesian Modeling and Inference for Massive Spatial Datasets.

Rajarshi Guhaniyogi, Sudipto Banerjee

Technometrics, 2018

2017

Convergence rate of Bayesian supervised tensor modeling with multiway shrinkage priors.

Rajarshi Guhaniyogi

J. Multivar. Anal., 2017

Bayesian Tensor Regression.

Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson

J. Mach. Learn. Res., 2017

2016

Compressed Gaussian Process for Manifold Regression.

Rajarshi Guhaniyogi, David B. Dunson

J. Mach. Learn. Res., 2016

2014

Bayesian Conditional Density Filtering for Big Data.

Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson

CoRR, 2014

2013

Bayesian Compressed Regression

Rajarshi Guhaniyogi, David B. Dunson

CoRR, 2013