43 citations · 90 across the 13 of their papers we have counts for
3 papers · 1 filter
Mean-field variational inference with the TAP free energy: Geometric and statistical properties in linear models
Michael Celentano, Zhou Fan, Licong Lin +1
We study mean-field variational inference in a Bayesian linear model when the sample size n is comparable to the dimension p. In high dimensions, the common approach of minimizing…
Challenges of the inconsistency regime: Novel debiasing methods for missing data models
Michael Celentano, Martin J. Wainwright
We study semi-parametric estimation of the population mean when data is observed missing at random (MAR) in the "inconsistency regime", in which neither the outcome model n…
Integral Probability Metrics Meet Neural Networks: The Radon-Kolmogorov-Smirnov Test
Seunghoon Paik, Michael Celentano, Alden Green +1
Integral probability metrics (IPMs) constitute a general class of nonparametric two-sample tests that are based on maximizing the mean difference between samples from one distribut…