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Bayesian learning using Gaussian processes provides a foundational framework for making decisions in a manner that balances what is known with what could be learned by gathering data. In this dissertation, we develop techniques for…

Machine Learning · Statistics 2022-04-29 Alexander Terenin

Examples with bound information on the regression function and density abound in many real applications. We propose a novel approach for estimating such functions by incorporating the prior knowledge on the bounds. Specially, a Gaussian…

Methodology · Statistics 2018-10-30 Jize Zhang , Lizhen Lin

We survey some recent regularity results for fractional p-Laplacian elliptic equations, especially focusing on pure and weighted boundary H\"older continuity of the solutions of related Dirichlet problems. Then, we present some applications…

Analysis of PDEs · Mathematics 2024-12-02 Antonio Iannizzotto

Many functions have approximately-known upper and/or lower bounds, potentially aiding the modeling of such functions. In this paper, we introduce Gaussian process models for functions where such bounds are (approximately) known. More…

Machine Learning · Computer Science 2022-10-20 Vu Nguyen , Marc Peter Deisenroth , Michael A. Osborne

Consider non-intersecting Brownian motions on the real line, starting from the origin at t=0, with a number of particles forced to reach p distinct target points at time t=1. This work shows that the transition probability, that is the…

Probability · Mathematics 2009-11-03 Mark Adler , Jonathan Delepine , Pierre van Moerbeke , Pol Vanhaecke

We derive explicit lower and upper bounds for the probability generating functional of a stationary locally stable Gibbs point process, which can be applied to summary statistics like the F function. For pairwise interaction processes we…

Probability · Mathematics 2013-04-18 Kaspar Stucki , Dominic Schuhmacher

We study well-posedness of sweeping processes with stochastic perturbations generated by a fractional Brownian motion and convergence of associated numerical schemes. To this end, we first prove new existence, uniqueness and approximation…

Classical Analysis and ODEs · Mathematics 2015-05-07 Adrian Falkowski , Leszek Slominski

This paper is concerned with various aspects of the Slepian process $(B_{t+1} - B_t, t \ge 0)$ derived from a one-dimensional Brownian motion $(B_t, t \ge 0 )$. In particular, we offer an analysis of the local structure of the Slepian zero…

Probability · Mathematics 2015-06-12 Jim Pitman , Wenpin Tang

A family of reflected Brownian motions is used to construct Dyson's process of non-colliding Brownian motions. A number of explicit formulae are given, including one for the distribution of a family of coalescing Brownian motions.

Probability · Mathematics 2007-05-23 Jon Warren

We consider the approximation of a convolution of possibly different probability measures by (compound) Poisson distributions and also by related signed measures of higher order. We present new total variation bounds having a better…

Probability · Mathematics 2017-03-08 Bero Roos

We show that some boundary conditions assumed at a thin membrane may result in normal diffusion not being the stochastic Markov process. We consider boundary conditions defined in terms of the Laplace transform in which there is a linear…

Statistical Mechanics · Physics 2020-08-26 Tadeusz Kosztołowicz

A sequential piecewise linear programming method is presented where bounded domains of non-convex functions are successively contracted about the solution of a piecewise linear program at each iteration of the algorithm. Although…

Optimization and Control · Mathematics 2020-04-21 James P. L. Tan

This note reports on a scheme for interpolating the boundary conditions be- tween non-adjacent modeling regions when the model is based on Monte-Carlo computations of a collection of particles. The scheme conserves particles in a natural…

Computational Physics · Physics 2007-05-23 C. W. Gear , Ioannis G. Kevrekidis

We present a method of solving a nonlinear Dirichlet problem with discontinuous boundary data and we give a probabilistic representation of the solution using the nonlocal branching process associated with the nonlinear term of the…

Probability · Mathematics 2024-10-23 Lucian Beznea , Oana Lupascu-Stamate , Alexandra Teodor

Gaussian processes are powerful non-parametric probabilistic models for stochastic functions. However, the direct implementation entails a complexity that is computationally intractable when the number of observations is large, especially…

We consider the asymmetric simple exclusion process confined to the nonnegative integers with an open boundary at 0. The point 0 is connected to a reservoir where particles are injected and ejected at prescribed rates subject to the…

Probability · Mathematics 2013-10-08 Craig A. Tracy , Harold Widom

In this paper, we aim to study solutions of reflected generalized BSDEs, involving the integral with respect to a continuous process, which is the local time of the diffusion on the boundary. We consider both a finite random terminal and a…

Probability · Mathematics 2010-11-16 Auguste Aman , Abouo Elouaflin , Modeste N'zi

A compound Poisson process whose randomized time is an independent Poisson process is called compound Poisson process with Poisson subordinator. We provide its probability distribution, which is expressed in terms of the Bell polynomials,…

Probability · Mathematics 2015-11-18 Antonio Di Crescenzo , Barbara Martinucci , Shelemyahu Zacks

We study a nonlocal diffusion operator in a bounded smooth domain prescribing the flux through the boundary. This problem may be seen as a generalization of the usual Neumann problem for the heat equation. First, we prove existence,…

Analysis of PDEs · Mathematics 2007-05-23 C. Cortazar , M. Elgueta , J. D. Rossi , N. Wolanski

In this paper, we introduce polynomial time algorithms that generate random $k$-noncrossing partitions and 2-regular, $k$-noncrossing partitions with uniform probability. A $k$-noncrossing partition does not contain any $k$ mutually…

Combinatorics · Mathematics 2009-11-17 Jing Qin , Christian M. Reidys
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