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ORCIDRajarshi Guhaniyogi
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2020 – today
- 2024
[j8]Sharmistha Guha
, Rajarshi Guhaniyogi:
Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data. Technometrics 66(3): 422-437 (2024)- [i3]Bowen Lei, Rajarshi Guhaniyogi, Krishnendu Chandra, Aaron Scheffler, Bani K. Mallick:
InVA: Integrative Variational Autoencoder for Harmonization of Multi-modal Neuroimaging Data. CoRR abs/2402.02734 (2024) - 2022
- [j7]Rajarshi Guhaniyogi, Cheng Li, Terrance D. Savitsky, Sanvesh Srivastava:
Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior. J. Mach. Learn. Res. 23: 84:1-84:59 (2022) - [j6]Rene Gutierrez, Rajarshi Guhaniyogi:
Bayesian Dynamic Feature Partitioning in High-Dimensional Regression With Big Data. Technometrics 64(2): 224-240 (2022) - 2021
- [j5]Sharmistha Guha, Rajarshi Guhaniyogi:
Bayesian Generalized Sparse Symmetric Tensor-on-Vector Regression. Technometrics 63(2): 160-170 (2021) - 2020
- [c1]Rajarshi Guhaniyogi:
High Dimensional Bayesian Regularization in Regressions Involving Symmetric Tensors. IPMU (3) 2020: 347-357
2010 – 2019
- 2018
- [j4]Rajarshi Guhaniyogi, Sudipto Banerjee:
Meta-Kriging: Scalable Bayesian Modeling and Inference for Massive Spatial Datasets. Technometrics 60(4): 430-444 (2018) - 2017
- [j3]Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson:
Bayesian Tensor Regression. J. Mach. Learn. Res. 18: 79:1-79:31 (2017) - [j2]Rajarshi Guhaniyogi:
Convergence rate of Bayesian supervised tensor modeling with multiway shrinkage priors. J. Multivar. Anal. 160: 157-168 (2017) - 2016
- [j1]Rajarshi Guhaniyogi, David B. Dunson:
Compressed Gaussian Process for Manifold Regression. J. Mach. Learn. Res. 17: 69:1-69:26 (2016) - 2014
- [i2]Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson:
Bayesian Conditional Density Filtering for Big Data. CoRR abs/1401.3632 (2014) - 2013
- [i1]Rajarshi Guhaniyogi, David B. Dunson:
Bayesian Compressed Regression. CoRR abs/1303.0642 (2013)
Coauthor Index
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