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20212026
most citedA Unifying Approach to Distributional Limits for Empirical Optimal Transport

13 citations · 23 across the 7 of their papers we have counts for

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6 papers · 1 filter

math.ST2025

Sharp Convergence Rates of Empirical Unbalanced Optimal Transport for Spatio-Temporal Point Processes

Marina Struleva, Shayan Hundrieser, Dominic Schuhmacher +1

We statistically analyze empirical plug-in estimators for unbalanced optimal transport (UOT) formalisms, focusing on the Kantorovich-Rubinstein distance, between general intensity…

math.ST2025

Optimal Transport Based Testing in Factorial Designs

Michel Groppe, Linus Niemöller, Shayan Hundrieser +4

We introduce a general framework for testing statistical hypotheses in factorial designs for probability measures supported on finite spaces. The suggested methodology is based on…

math.ST2025

Local Poisson Deconvolution for Discrete Signals

Shayan Hundrieser, Tudor Manole, Danila Litskevich +1

We analyze the statistical problem of recovering an atomic signal, modeled as a discrete uniform distribution , from a binned Poisson convolution model. This question is motivat…

math.ST2024

A Lower Bound for Estimating Fréchet Means

Shayan Hundrieser, Benjamin Eltzner, Stephan F. Huckemann

Fréchet means, conceptually appealing, generalize the Euclidean expectation to general metric spaces. We explore how well Fréchet means can be estimated from independent and identi…

math.ST202210 cited

Empirical Optimal Transport between Different Measures Adapts to Lower Complexity

Shayan Hundrieser, Thomas Staudt, Axel Munk

The empirical optimal transport (OT) cost between two probability measures from random data is a fundamental quantity in transport based data analysis. In this work, we derive nove…

math.ST2021

Finite Sample Smeariness on Spheres

Benjamin Eltzner, Shayan Hundrieser, Stephan F. Huckemann

Finite Sample Smeariness (FSS) has been recently discovered. It means that the distribution of sample Fréchet means of underlying rather unsuspicious random variables can behave as…