Anindya Bhadra

发表

Integrative sparse Bayesian analysis of high-dimensional multi-platform genomic data in glioblastoma

Veerabhadran Baladandayuthapani, Anindya Bhadra, 2013, 2013 IEEE International Workshop on Genomic Signal Processing and Statistics.

Bayesian feature selection in high‐dimensional regression in presence of correlated noise

Guy Feldman, Sergey Kirshner, Anindya Bhadra, 2014 .

Time Series Analysis for Nonlinear Dynamical Systems with Applications to Modeling of Infectious Diseases.

Anindya Bhadra, A. Bhadra, 2010 .

Malaria in Northwest India: Data Analysis via Partially Observed Stochastic Differential Equation Models Driven by Lévy Noise

Anindya Bhadra, Edward L. Ionides, Karina Laneri, 2011 .

Nonparametric Bayesian Approaches to Non-homogeneous Hidden Markov Models

Bani K. Mallick, Abhra Sarkar, Anindya Bhadra, 2012, 1205.1839.

Default Bayesian Analysis with Global-Local Shrinkage Priors

Nicholas G. Polson, Anindya Bhadra, Jyotishka Datta, 2015, 1510.03516.

Lasso Meets Horseshoe: A Survey

Nicholas G. Polson, Anindya Bhadra, Jyotishka Datta, 2017, Statistical Science.

Bayesian Variable Selection in Multivariate Nonlinear Regression with Graph Structures

Bani K. Mallick, Veerabhadran Baladandayuthapani, Nilabja Guha, 2020, 2010.14638.

Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems

Raymond J. Carroll, Anindya Bhadra, R. Carroll, 2016, Stat. Comput..

Adaptive particle allocation in iterated sequential Monte Carlo via approximating meta-models

Edward L. Ionides, Anindya Bhadra, 2016, Stat. Comput..

Joint Mean-Covariance Estimation via the Horseshoe with an Application in Genomic Data Analysis

Yunfan Li, Anindya Bhadra, Bruce A. Craig, 2019, 1903.06768.

Horseshoe Regularisation for Machine Learning in Complex and Deep Models 1

Yunfan Li, Nicholas G. Polson, Anindya Bhadra, 2019, International Statistical Review.

Divide and Recombine for Large and Complex Data: Model Likelihood Functions Using MCMC and TRMM Big Data Analysis

Qi Liu, William S. Cleveland, Anindya Bhadra, 2018, 1801.05007.

The Horseshoe-Like Regularization for Feature Subset Selection

Nicholas G. Polson, Anindya Bhadra, Jyotishka Datta, 2019, Sankhya B.

Inferring network structure in non‐normal and mixed discrete‐continuous genomic data

Veerabhadran Baladandayuthapani, Anindya Bhadra, Arvind Rao, 2016, Biometrics.

Forcing Versus Feedback: Epidemic Malaria and Monsoon Rains in Northwest India

Mercedes Pascual, Edward L. Ionides, Karina Laneri, 2010, PLoS Comput. Biol..

Prediction Risk for the Horseshoe Regression

Nicholas G. Polson, Anindya Bhadra, Yunfan Li, 2016, J. Mach. Learn. Res..

Precision matrix estimation under the horseshoe-like prior–penalty dual

Anindya Bhadra, Jyotishka Datta, Sayantan Banerjee, 2021, Electronic Journal of Statistics.

Bayesian Robust Learning in Chain Graph Models for Integrative Pharmacogenomics

Veerabhadran Baladandayuthapani, Anindya Bhadra, Min Jin Ha, 2021, 2111.11529.

Joint mean-covariance estimation via the horseshoe

Anindya Bhadra, Bruce A. Craig, Jyotishka Datta, 2021, J. Multivar. Anal..

Merging Two Cultures: Deep and Statistical Learning pdf

Vadim Sokolov, Nicholas G. Polson, Anindya Bhadra, 2021, WIREs Computational Statistics.

Global-Local Mixtures

Nicholas G. Polson, Anindya Bhadra, Jyotishka Datta, 2016, 1604.07487.

Global-Local Mixtures: A Unifying Framework

Nicholas G. Polson, Anindya Bhadra, Jyotishka Datta, 2020, Sankhya A.

Prediction risk for global-local shrinkage regression

Nicholas G. Polson, Anindya Bhadra, Jyotishka Datta, 2016 .

The Graphical Horseshoe Estimator for Inverse Covariance Matrices

Anindya Bhadra, Bruce A. Craig, Yunfan Li, 2017, Journal of Computational and Graphical Statistics.

An expectation–maximization scheme for measurement error models

Anindya Bhadra, A. Bhadra, 2017 .

Joint High‐Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis

Bani K Mallick, Anindya Bhadra, B. Mallick, 2013, Biometrics.