65 citations · 86 across the 27 of their papers we have counts for
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Normal approximations in nonparametric empirical Bayes
Jiafeng Chen, Nabarun Deb, Nikolaos Ignatiadis
Empirical Bayes analyses routinely model noisy measurements of latent parameters as normal, justifying this by an informal appeal to the central limit theorem (CLT). This paper put…
Compound decisions and empirical Bayes via Bayesian nonparametrics
Nikolaos Ignatiadis, Sid Kankanala
We study compound decision theory from a nonparametric Bayesian perspective, with particular emphasis on their relationship to empirical Bayes (EB) procedures. Motivated by the sha…
Stein's unbiased risk estimate and Hyvärinen's score matching
Sulagna Ghosh, Nikolaos Ignatiadis, Frederic Koehler +1
Given a collection of observed signals corrupted with Gaussian noise, how can we learn to optimally denoise them? This fundamental problem arises in both empirical Bayes and genera…
Interpretation of local false discovery rates under the zero assumption
Daniel Xiang, Nikolaos Ignatiadis, Peter McCullagh
In large-scale studies with parallel signal-plus-noise observations, the local false discovery rate is a summary statistic that is often presumed to be equal to the posterior proba…
Empirical partially Bayes multiple testing and compound decisions
Nikolaos Ignatiadis, Bodhisattva Sen
A common task in high-throughput biology is to screen for associations across thousands of units of interest, e.g., genes or proteins. Often, the data for each unit are modeled as…