| Gibbs sampling, exponential families and orthogonal polynomials P Diaconis, K Khare, L Saloff-Coste | 155 | 2008 |
| A convex pseudolikelihood framework for high dimensional partial correlation estimation with convergence guarantees K Khare, SY Oh, B Rajaratnam Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2015 | 154 | 2015 |
| Wishart distributions for decomposable covariance graph models K Khare, B Rajaratnam | 86 | 2011 |
| Posterior graph selection and estimation consistency for high-dimensional Bayesian DAG models X Cao, K Khare, M Ghosh | 73 | 2019 |
| Geometric ergodicity of the Bayesian lasso K Khare, JP Hobert | 58 | 2013 |
| High-dimensional posterior consistency in Bayesian vector autoregressive models S Ghosh, K Khare, G Michailidis Journal of the American Statistical Association, 2019 | 53 | 2019 |
| Geometric ergodicity of the Gibbs sampler for Bayesian quantile regression K Khare, JP Hobert Journal of Multivariate Analysis 112, 108-116, 2012 | 51 | 2012 |
| Rates of convergence of some multivariate Markov chains with polynomial eigenfunctions K Khare, H Zhou | 50 | 2009 |
| A spectral analytic comparison of trace-class data augmentation algorithms and their sandwich variants K Khare, JP Hobert | 49 | 2011 |
| A Bayesian approach for envelope models K Khare, S Pal, Z Su | 48 | 2017 |
| Geometric ergodicity for Bayesian shrinkage models S Pal, K Khare | 42 | 2014 |
| High dimensional posterior convergence rates for decomposable graphical models R Xiang, K Khare, M Ghosh | 39 | 2015 |
| RasGRP1 promotes amphetamine-induced motor behavior through a Rhes interaction network (“Rhesactome”) in the striatum N Shahani, S Swarnkar, V Giovinazzo, J Morgenweck, LM Bohn, ... Science signaling 9 (454), ra111-ra111, 2016 | 38 | 2016 |
| Optimization methods for sparse pseudo-likelihood graphical model selection S Oh, O Dalal, K Khare, B Rajaratnam Advances in Neural Information Processing Systems 27, 2014 | 32 | 2014 |
| Stochastic alternating projections P Diaconis, K Khare, L Saloff-Coste Illinois Journal of Mathematics 54 (3), 963-979, 2010 | 31 | 2010 |
| High-dimensional posterior consistency for hierarchical non-local priors in regression X Cao, K Khare, M Ghosh | 29 | 2020 |
| Gibbs sampling, conjugate priors and coupling P Diaconis, K Khare, L Saloff-Coste Sankhya A 72, 136-169, 2010 | 29 | 2010 |
| A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data K Khare, SY Oh, S Rahman, B Rajaratnam Machine Learning 108, 2061-2086, 2019 | 24 | 2019 |
| Convergence properties of Gibbs samplers for Bayesian probit regression with proper priors S Chakraborty, K Khare | 22 | 2017 |
| Uncertainty quantification for modern high-dimensional regression via scalable Bayesian methods B Rajaratnam, D Sparks, K Khare, L Zhang Journal of Computational and Graphical Statistics 28 (1), 174-184, 2019 | 19 | 2019 |
Bala RajaratnamUniversity of California, DavisVerified email at ucdavis.edu
