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Nonparametric Riemannian Empirical Bayes, and Denoising Measurements on Manifolds
Adam Quinn Jaffe, Leonardo V. Santoro, Bodhisattva Sen
We initiate the study of nonparametric empirical Bayes denoising methods in the setting where both the latent variables and their measurements lie on a compact Riemannian manifold,…
Empirical Bayes Estimation and Inference via Smooth Nonparametric Maximum Likelihood
Taehyun Kim, Bodhisattva Sen
The empirical Bayes -modeling approach based on the nonparametric maximum likelihood estimator (NPMLE) has been central to large-scale estimation and inference in the normal mea…
Distribution-free Measures of Association based on Optimal Transport
Nabarun Deb, Promit Ghosal, Bodhisattva Sen
In this paper we propose and study a class of nonparametric, yet interpretable measures of association between two random vectors and taking values in an…
Optimal Confidence Bands for Shape-restricted Regression in Multidimensions
Ashley, Datta, Somabha Mukherjee +1
In this paper, we propose and study construction of confidence bands for shape-constrained regression functions when the predictor is multivariate. In particular, we consider the c…
A New Perspective On Denoising Based On Optimal Transport
Nicolas Garcia Trillos, Bodhisattva Sen
In the standard formulation of the denoising problem, one is given a probabilistic model relating a latent variable and an observation $Z \…