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20212026
most citedOn the Robustness to Misspecification of -Posteriors and Their Variational Approximations

3 citations · 4 across the 10 of their papers we have counts for

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7 papers · 1 filter

math.ST2026

The Influence Function of Transport-based Quantiles

Alberto González-Sanz, Shunan Sheng, Bohan Wu +1

Transport-based quantiles extend univariate quantiles to multivariate distributions via optimal transport. We study the influence function of the transport quantile map $\mathbf{Q}…

math.ST2026

The Threshold Breakdown Point

Tianjun Ke, Marco Avella Medina

We introduce a novel approach to finite sample robustness that avoids the pessimism of traditional breakdown analyses. We define the threshold breakdown point, the smallest contami…

math.ST2026

Breakdown properties of optimal transport maps: general transportation costs

Alberto Gonzalez-Sanz, Marco Avella Medina

Two recent works, Avella-Medina and González-Sanz (2026) and Passeggeri and Paindaveine (2026), studied the robustness of the optimal transport map through its breakdown point, i.e…

math.ST2026

Differentially Private Inference for Longitudinal Linear Regression

Getoar Sopa, Marco Avella Medina, Cynthia Rush

Differential Privacy (DP) provides a rigorous framework for releasing statistics while protecting individual information present in a dataset. Although substantial progress has bee…

math.ST2026

Statistical Guarantees for Data-driven Posterior Tempering

Ruchira Ray, Marco Avella Medina, Cynthia Rush

Posterior tempering reduces the influence of the likelihood in the calculation of the posterior by raising the likelihood to a fractional power . The resulting power posterior -…

math.ST2025

A theoretical framework for M-posteriors: frequentist guarantees and robustness properties

Juraj Marusic, Marco Avella Medina, Cynthia Rush

We provide a theoretical framework for a wide class of generalized posteriors that can be viewed as the natural Bayesian posterior counterpart of the class of M-estimators in the f…

math.ST2023★ 1 cited

Asymptotics for power posterior mean estimation

Ruchira Ray, Marco Avella Medina, Cynthia Rush

Power posteriors "robustify" standard Bayesian inference by raising the likelihood to a constant fractional power, effectively downweighting its influence in the calculation of the…