68 citations · 353 across the 57 of their papers we have counts for
5 papers · 1 filter
Optimal Gaussian approximations to the posterior for log-linear models with Diaconis-Ylvisaker priors
James E. Johndrow, Anirban Bhattacharya
In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solu…
Scalable Bayesian Variable Selection Using Nonlocal Prior Densities in Ultrahigh-Dimensional Settings
Minsuk Shin, Anirban Bhattacharya, Valen E. Johnson
Bayesian model selection procedures based on nonlocal alternative prior densities are extended to ultrahigh dimensional settings and compared to other variable selection procedures…
Fast sampling with Gaussian scale-mixture priors in high-dimensional regression
Anirban Bhattacharya, Antik Chakraborty, Bani K. Mallick
We propose an efficient way to sample from a class of structured multivariate Gaussian distributions which routinely arise as conditional posteriors of model parameters that are as…
Optimal Bayesian estimation in stochastic block models
Debdeep Pati, Anirban Bhattacharya
With the advent of structured data in the form of social networks, genetic circuits and protein interaction networks, statistical analysis of networks has gained popularity over re…
Posterior contraction in Gaussian process regression using Wasserstein approximations
Anirban Bhattacharya, Debdeep Pati
We study posterior rates of contraction in Gaussian process regression with unbounded covariate domain. Our argument relies on developing a Gaussian approximation to the posterior…