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We consider the symmetric inclusion process on a general finite graph. Our main result establishes universal upper and lower bounds for the spectral gap of this interacting particle system in terms of the spectral gap of the random walk on…

Probability · Mathematics 2025-12-09 Seonwoo Kim , Federico Sau

This paper considers a probabilistic model for floating-point computation in which the roundoff errors are represented by bounded random variables with mean zero. Using this model, a probabilistic bound is derived for the forward error of…

Numerical Analysis · Mathematics 2021-04-15 Eric Hallman

The method for computation of conditional probability density function for the nonlinear Schr\"odinger equation with additive noise is developed. We present in a constructive form the conditional probability density function in the limit of…

Information Theory · Computer Science 2014-11-26 I. S. Terekhov , S. S. Vergeles , S. K. Turitsyn

This paper proposes a Sequential Monte Carlo approach for the Bayesian estimation of mixed causal and noncausal models. Unlike previous Bayesian estimation methods developed for these models, Sequential Monte Carlo offers extensive…

Econometrics · Economics 2025-01-08 Gianluca Cubadda , Francesco Giancaterini , Stefano Grassi

In probabilistic program analysis, quantitative analysis aims at deriving tight numerical bounds for probabilistic properties such as expectation and assertion probability. Most previous works consider numerical bounds over the whole…

Programming Languages · Computer Science 2026-01-06 Tengshun Yang , Shenghua Feng , Hongfei Fu , Naijun Zhan , Jingyu Ke , Shiyang Wu

Exact formulas are derived for the probability density functions of the sum and difference of two independent non-central gamma distributed random variables, with both series and integral representations of the density presented. These…

Probability · Mathematics 2026-05-18 Robert E. Gaunt , Heather L. Sutcliffe

In this paper, we develop a series of boundary pointwise regularity for Dirichlet problems and oblique derivative problems. As applications, we give direct and simple proofs of the higher regularity of the free boundaries in obstacle-type…

Analysis of PDEs · Mathematics 2022-04-26 Yuanyuan Lian , Kai Zhang

We provide an algorithm to generate trajectories of sparse stochastic processes that are solutions of linear ordinary differential equations driven by L\'evy white noises. A recent paper showed that these processes are limits in law of…

Statistics Theory · Mathematics 2020-08-10 Leello Dadi , Shayan Aziznejad , Michael Unser

The theory of Chebyshev approximation has been extensively studied. In most cases, the optimality conditions are based on the notion of alternance or alternating sequence (that is, maximal deviation points with alternating deviation signs).…

Functional Analysis · Mathematics 2025-01-30 Nadezda Sukhorukova , Julien Ugon

We consider the integration of two-dimensional, piecewise constant functions with respect to copulas. By drawing a connection to linear assignment problems, we can give optimal upper and lower bounds for such integrals and construct the…

Optimization and Control · Mathematics 2016-11-26 Markus Hofer , Maria Rita Iacò

This paper is a step in the direction of understanding the behavior of non-intersecting Brownian motions on the real line, when the number of particles becomes large. Consider 2k non-intersecting Brownian motions, all starting at the…

Probability · Mathematics 2007-05-23 Mark Adler , Pierre van Moerbeke

In this work we consider time series with a finite number of discrete point changes. We assume that the data in each segment follows a different probability density functions (pdf). We focus on the case where the data in all segments are…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ali Mohammad-Djafari , Olivier Feron

We study a probabilistic numerical method for the solution of both boundary and initial value problems that returns a joint Gaussian process posterior over the solution. Such methods have concrete value in the statistics on Riemannian…

Machine Learning · Statistics 2014-02-13 Philipp Hennig , Søren Hauberg

We present sufficient conditions for sums of dependent point processes to converge in distribution to a Poisson process. This extends the classical result of Grigelionis [Theory Probab. Appl. 8 (1963) 172--182] for sums of uniformly null…

Probability · Mathematics 2007-05-23 Matthew O. Jones , Richard F. Serfozo

A conditioned stochastic process can display a very different behavior from the unconditioned process. In particular, a conditioned process can exhibit non-Gaussian fluctuations even if the unconditioned process is Gaussian. In this work,…

Statistical Mechanics · Physics 2021-03-18 Tristan Gautié , Naftali R. Smith

In this paper we consider the approximation of a function by its interpolating multilinear spline and the approximation of its derivatives by the derivatives of the corresponding spline. We derive formulas for the uniform approximation…

Numerical Analysis · Mathematics 2013-08-27 Ryan Anderson , Yuliya Babenko , Tetiana Leskevych

The paper reports on a recent construction of M-functions and Krein resolvent formulas for general closed extensions of an adjoint pair, and their implementation to boundary value problems for second-order strongly elliptic operators on…

Analysis of PDEs · Mathematics 2008-10-16 Gerd Grubb

In a previous work, we developed an algorithm for the computation of incomplete Bessel functions, which pose as a numerical challenge, based on the $G_{n}^{(1)}$ transformation and Slevinsky-Safouhi formula for differentiation. In the…

Numerical Analysis · Mathematics 2022-04-26 Richard M. Slevinsky , Hassan Safouhi

We find the formulas of the transition probabilities of the $N$-particle multi-species asymmetric simple exclusion processes (ASEP), and show that the transition probabilities are written as a determinant when the order of particles in the…

Mathematical Physics · Physics 2020-12-22 Eunghyun Lee

We propose a fast algorithm for the probabilistic solution of boundary value problems (BVPs), which are ordinary differential equations subject to boundary conditions. In contrast to previous work, we introduce a Gauss--Markov prior and…

Machine Learning · Statistics 2021-06-16 Nicholas Krämer , Philipp Hennig
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