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20112026
most citedPosterior contraction in sparse Bayesian factor models for massive covariance matrices

68 citations · 319 across the 71 of their papers we have counts for

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Showing 2017Show all

7 papers · 1 filter

math.ST2017★ 9 cited

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…

math.ST2017

-Variational Inference with Statistical Guarantees

Yun Yang, Debdeep Pati, Anirban Bhattacharya

We propose a family of variational approximations to Bayesian posterior distributions, called -VB, with provable statistical guarantees. The standard variational approximation i…

math.ST2017★ 36 cited

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…

stat.ME2017

Compressed Covariance Estimation With Automated Dimension Learning

Gautam Sabnis, Debdeep Pati, Anirban Bhattacharya

We propose a method for estimating a covariance matrix that can be represented as a sum of a low-rank matrix and a diagonal matrix. The proposed method compresses high-dimensional…

math.ST2017★ 1 cited

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…

math.ST2017★ 15 cited

Bayesian model selection consistency and oracle inequality with intractable marginal likelihood

Yun Yang, Debdeep Pati

In this article, we investigate large sample properties of model selection procedures in a general Bayesian framework when a closed form expression of the marginal likelihood funct…

stat.ME2017

A Two-Step Geometric Framework For Density Modeling

Sutanoy Dasgupta, Debdeep Pati, Anuj Srivastava

We introduce a novel two-step approach for estimating a probability density function (pdf) given its samples, with the second and important step coming from a geometric formulation…