The Gromov-Wasserstein (GW) distance quantifies discrepancy between metr...
We study statistical inference for the optimal transport (OT) map (also ...
f-divergences, which quantify discrepancy between probability
distributi...
Sliced Wasserstein distances preserve properties of classic Wasserstein
...
We study limit theorems for entropic optimal transport (EOT) maps, dual
...
This article reviews recent progress in high-dimensional bootstrap. We f...
Optimal transport (OT) is a versatile framework for comparing probabilit...
The Wasserstein distance is a metric on a space of probability measures ...
The smooth 1-Wasserstein distance (SWD) W_1^σ was recently proposed as
a...
In this paper, we establish a high-dimensional CLT for the sample mean o...
We develop a novel method of constructing confidence bands for nonparame...
Statistical distances, i.e., discrepancy measures between probability
di...
We consider inference for high-dimensional exchangeable arrays where the...
In this paper, we develop uniform inference methods for the conditional ...
Principled nonparametric tests for regression curvature in R^d
are often...
Statistical divergences are ubiquitous in machine learning as tools for
...
The 1-Wasserstein distance (W_1) is a popular proximity measure
between ...
This paper deals with the Gaussian and bootstrap approximations to the
d...
This paper derives Berry-Esseen bounds for an important class of non-sta...
Data in the form of networks are increasingly available in a variety of
...
We study the problem of distributional approximations to high-dimensiona...
In this paper, we consider estimation of the conditional mode of an outc...
This chapter presents key concepts and theoretical results for analyzing...
This chapter presents key concepts and theoretical results for analyzing...
In this paper, we study frequentist coverage errors of Bayesian credible...
This paper studies inference for the mean vector of a high-dimensional
U...
The purpose of this note is to provide a detailed proof of Nazarov's
ine...