36 citations · 54 across the 8 of their papers we have counts for
9 papers
On Statistical Optimality of Variational Bayes
Debdeep Pati, Anirban Bhattacharya, Yun Yang
The article addresses a long-standing open problem on the justification of using variational Bayes methods for parameter estimation. We provide general conditions for obtaining opt…
Frequentist coverage and sup-norm convergence rate in Gaussian process regression
Yun Yang, Anirban Bhattacharya, Debdeep Pati
Gaussian process (GP) regression is a powerful interpolation technique due to its flexibility in capturing non-linearity. In this paper, we provide a general framework for understa…
Adaptive posterior convergence rates in non-linear latent variable models
Shuang Zhou, Debdeep Pati, Anirban Bhattacharya +1
Non-linear latent variable models have become increasingly popular in a variety of applications. However, there has been little study on theoretical properties of these models. In…
Sparse additive Gaussian process with soft interactions
Garret Vo, Debdeep Pati
Additive nonparametric regression models provide an attractive tool for variable selection in high dimensions when the relationship between the response and predictors is complex.…
Sub-optimality of some continuous shrinkage priors
Anirban Bhattacharya, David B. Dunson, Debdeep Pati +1
Two-component mixture priors provide a traditional way to induce sparsity in high-dimensional Bayes models. However, several aspects of such a prior, including computational comple…
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…