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Found 4 papers, 2 papers with code
Empirical Bayes mean estimation with nonparametric errors via order statistic regression on replicated data
We study empirical Bayes estimation of the effect sizes of $N$ units from $K$ noisy observations on each unit.
Methodology
Two-component Mixture Model in the Presence of Covariates
We propose a tuning parameter-free nonparametric maximum likelihood approach, implementable via the EM algorithm, to estimate the unknown parameters.
Methodology
On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising
We study the Nonparametric Maximum Likelihood Estimator (NPMLE) for estimating Gaussian location mixture densities in $d$-dimensions from independent observations.
Sharp Inequalities for $f$-divergences
$f$-divergences are a general class of divergences between probability measures which include as special cases many commonly used divergences in probability, mathematical statistics and information theory such as Kullback-Leibler divergence, chi-squared divergence, squared Hellinger distance, total variation distance etc.
