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09/29/2022
How good is your Gaussian approximation of the posterior? Finite-sample computable error bounds for a variety of useful divergences
The Bayesian Central Limit Theorem (BCLT) for finite-dimensional models,...
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11/30/2020
An Automatic Finite-Sample Robustness Metric: Can Dropping a Little Data Change Conclusions?
We propose a method to assess the sensitivity of econometric analyses to...
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07/28/2019
A Higher-Order Swiss Army Infinitesimal Jackknife
Cross validation (CV) and the bootstrap are ubiquitous model-agnostic to...
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10/15/2018
Evaluating Sensitivity to the Stick Breaking Prior in Bayesian Nonparametrics
A central question in many probabilistic clustering problems is how many...
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06/01/2018
Return of the Infinitesimal Jackknife
The error or variability of machine learning algorithms is often assesse...
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01/31/2018
Cataloging the Visible Universe through Bayesian Inference at Petascale
Astronomical catalogs derived from wide-field imaging surveys are an imp...
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12/05/2017
Measuring Cluster Stability for Bayesian Nonparametrics Using the Linear Bootstrap
Clustering procedures typically estimate which data points are clustered...
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11/10/2016
Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference
Celeste is a procedure for inferring astronomical catalogs that attains ...
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06/23/2016
Fast robustness quantification with variational Bayes
Bayesian hierarchical models are increasing popular in economics. When u...
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06/12/2015
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes
Mean field variational Bayes (MFVB) is a popular posterior approximation...
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02/26/2015
Covariance Matrices and Influence Scores for Mean Field Variational Bayes
Mean field variational Bayes (MFVB) is a popular posterior approximation...
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10/24/2014