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Conformal prediction provides finite-sample, distribution-free coverage under exchangeability, but standard constructions may lack robustness in the presence of outliers or heavy tails. We propose a robust conformal method based on a…

Statistics Theory · Mathematics 2026-04-21 Alejandro Cholaquidis , Emilien Joly , Leonardo Moreno

We discuss a method to estimate the measure of a compact set which is approximated using the Hausdorff distance by a sequence of compact sets. We do this by considering corresponding fattenings of the sequence of compact sets and showing…

Spectral Theory · Mathematics 2025-12-01 Lior Tenenbaum

In this paper we prove matching upper and lower bounds for the transition density function of the subordinate reflected Brownian motion on fractals.

Probability · Mathematics 2021-06-02 Hubert Balsam

Obtaining reliable and precise estimates of wildlife species abundance and distribution is essential for the conservation and management of animal populations and natural reserves. Spatial capture-recapture (SCR) models provide estimates of…

We consider the reflected entropy and the associated entanglement spectrum for free fermions reduced to two intervals in 1+1 dimensions. Working directly in the continuum theory the reflected entropy can be extracted from the spectrum of a…

High Energy Physics - Theory · Physics 2023-03-22 Souvik Dutta , Thomas Faulkner , Simon Lin

We construct a family of SDEs whose solutions select a reflected Brownian flow as well as a stochastic damped transport process (W\_t). The latter gives a representation for the solutions to the heat equation for differential 1-forms with…

Probability · Mathematics 2017-02-01 Marc Arnaudon , Xue-Mei Li

We study a Schilder-type large deviation principle for sticky-reflected Brownian motion with boundary diffusion, both at the static and sample path level in the short-time limit. A sharp transition for the rate function occurs, depending on…

Analysis of PDEs · Mathematics 2025-01-22 Jean-Baptiste Casteras , Leonard Monsaingeon , Luca Nenna

Image analysis frequently deals with shape estimation and image reconstruction. The ob jects of interest in these problems may be thought of as random sets, and one is interested in finding a representative, or expected, set. We consider a…

Methodology · Statistics 2011-06-09 Hanna K. Jankowski , Larissa I. Stanberry

We introduce a simulation-based, amortised Bayesian inference scheme to infer the parameters of random walks. Our approach learns the posterior distribution of the walks' parameters with a likelihood-free method. In the first step a graph…

Machine Learning · Computer Science 2022-12-07 Hippolyte Verdier , François Laurent , Alhassan Cassé , Christian Vestergaard , Jean-Baptiste Masson

We use recent results on the Fourier analysis of the zero sets of Brownian motion to explore the diophantine properties of an algorithmically random Brownian motion (also known as a complex oscillation). We discuss the construction and…

Logic in Computer Science · Computer Science 2014-09-08 Willem L. Fouche

Tracking on the rotation group is a key component of many modern systems for estimation of the motion of rigid bodies. To address this problem, here we describe a Bayesian algorithm that relies on directional measurements for tracking on…

Signal Processing · Electrical Eng. & Systems 2020-03-26 Sofia Suvorova , Stephen D. Howard , Bill Moran

In this paper, we consider adaptive estimation of an unknown planar compact, convex set from noisy measurements of its support function on a uniform grid. Both the problem of estimating the support function at a point and that of estimating…

Statistics Theory · Mathematics 2015-08-18 Tony Cai , Adityanand Guntuboyina , Yuting Wei

We investigate reflected random walks in the quarter plane, with particular emphasis on the time spent along the reflection boundary axes. Assuming the drift of the random walk lies within the cone, the local time converges -- without the…

Probability · Mathematics 2025-07-08 Viet Hung Hoang , Kilian Raschel

Given i.i.d samples from some unknown continuous density on hyper-rectangle $[0, 1]^d$, we attempt to learn a piecewise constant function that approximates this underlying density non-parametrically. Our density estimate is defined on a…

Machine Learning · Statistics 2015-09-24 Kun Yang , Hao Su , Wing Hung Wang

In this paper we investigate three discrete or semi-discrete approximation schemes for reflected Brownian motion on bounded Euclidean domains. For a class of bounded domains $D$ in $\mathbb{R}^n$ that includes all bounded Lipschitz domains…

Probability · Mathematics 2009-09-29 Krzysztof Burdzy , Zhen-Qing Chen

This paper develops the first method for the exact simulation of reflected Brownian motion (RBM) with non-stationary drift and infinitesimal variance. The running time of generating exact samples of non-stationary RBM at any time $t$ is…

Probability · Mathematics 2013-12-30 Mohammad Mousavi , Peter W. Glynn

We study pathwise approximation of scalar stochastic differential equations at a single point. We provide the exact rate of convergence of the minimal errors that can be achieved by arbitrary numerical methods that are based (in a…

Probability · Mathematics 2007-05-23 Thomas Muller-Gronbach

We present the first exact simulation method for multidimensional reflected Brownian motion (RBM). Exact simulation in this setting is challenging because of the presence of correlated local-time-like terms in the definition of RBM. We…

Probability · Mathematics 2017-08-31 Jose Blanchet , Karthyek R. A. Murthy

Density estimates based on point processes are often restrained to regions with irregular boundaries or holes. We propose a density estimator, the lattice-based density estimator, which produces reasonable density estimates under these…

Methodology · Statistics 2010-10-19 Ronald P. Barry , Julie McIntyre

In this paper we consider the Brownian motion with jump boundary and present a new proof of a recent result of Li, Leung and Rakesh concerning the exact convergence rate in the one-dimensional case. Our methods are different and mainly…

Probability · Mathematics 2011-01-20 Martin Kolb , Achim Wübker