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Related papers: Constraint Ornstein-Uhlenbeck bridges

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We study stochastic processes in which the trajectories are constrained so that the process realises a large deviation of the unconstrained process. In particular we consider stochastic bridges and the question of inequivalence of path…

Statistical Mechanics · Physics 2015-12-15 J. Szavits-Nossan , M. R. Evans

This paper presents a study of the properties of the Ornstein-Uhlenbeck bridge, specifically, we derive its Karhunen-Lo\`eve expansion for any value of the initial variance and mean-reversion parameter (or mean-repulsion if negative). We…

Probability · Mathematics 2014-01-23 Sylvain Corlay

We propose a novel stochastic method to generate Brownian paths conditioned to start at an initial point and end at a given final point during a fixed time $t_{f}$ under a given potential $U(x)$. These paths are sampled with a probability…

Statistical Mechanics · Physics 2016-11-24 Marc Delarue , Patrice Koehl , Henri Orland

We propose a novel stochastic method to generate paths conditioned to start in an initial state and end in a given final state during a certain time $t_{f}$. These paths are weighted with a probability given by the overdamped Langevin…

Statistical Mechanics · Physics 2015-05-27 Henri Orland

We refer by threshold Ornstein-Uhlenbeck to a continuous-time threshold autoregressive process. It follows the Ornstein-Uhlenbeck dynamics when above or below a fixed level, yet at this level (threshold) its coefficients can be…

Probability · Mathematics 2022-06-07 Sara Mazzonetto , Paolo Pigato

We study sample path deviations of the Wiener process from three different representations of its bridge: anticipative version, integral representation and space-time transform. Although these representations of the Wiener bridge are equal…

Probability · Mathematics 2014-03-25 Matyas Barczy , Peter Kern

The Ornstein-Uhlenbeck process can be seen as a paradigm of a finite-variance and statistically stationary rough random walk. Furthermore, it is defined as the unique solution of a Markovian stochastic dynamics and shares the same local…

Probability · Mathematics 2021-10-05 Laurent Chevillard , Marc Lagoin , Stephane G. Roux

A formula for the transition density of a Markov process defined by an infinite-dimensional stochastic equation is given in terms of the Ornstein--Uhlenbeck bridge and a useful lower estimate on the density is provided. As a consequence,…

Probability · Mathematics 2007-05-23 B. Goldys , B. Maslowski

It is considered Ornstein-Uhlenbeck process $ x_t = x_0 e^{-\theta t} + \mu (1-e^{-\theta t}) + \sigma \int_0^t e^{-\theta (t-s)} dW_s$, where $x_0 \in R$, $\theta>0$, $ \mu \in R$ and $\sigma > 0$ are parameters. By use values $(z_k)_{k…

Statistics Theory · Mathematics 2016-08-30 Levan Labadze , Gogi Pantsulaia

The purpose of the present work is to expand substantially the type of control and estimation problems that can be addressed following the paradigm of Schr\"odinger bridges, by incorporating termination (killing) of stochastic flows.…

Optimization and Control · Mathematics 2024-06-24 Asmaa Eldesoukey , Olga Movilla Miangolarra , Tryphon T. Georgiou

We propose a method to exactly generate bridge run-and-tumble trajectories that are constrained to start at the origin with a given velocity and to return to the origin after a fixed time with another given velocity. The method extends the…

Statistical Mechanics · Physics 2021-09-22 Benjamin De Bruyne , Satya N. Majumdar , Gregory Schehr

This paper motivates the use of random-bridges -- stochastic processes conditioned to take target distributions at fixed timepoints -- in the realm of generative modelling. Herein, random-bridges can act as stochastic transports between two…

Machine Learning · Computer Science 2026-04-07 Stefano Goria , Levent A. Mengütürk , Murat C. Mengütürk , Berkan Sesen

We set forth a new method for generating model-agnostic, nonparametric priors for neutron star equation-of-state inference that are stable, causal and thermodynamically consistent by construction. This generalizes Gaussian processes to…

High Energy Astrophysical Phenomena · Physics 2026-05-12 Tyler Gorda , Oleg Komoltsev , Aleksi Kurkela , Eirik Sunde

The small noise cut-off phenomenon in continuous time and space has been studied in the recent literature for the linear and non-linear stable Langevin dynamics with additive L\'evy drivers - understood as abrupt thermalization of the…

Probability · Mathematics 2025-02-13 Gerardo Barrera , Michael A. Högele , Pauliina Ilmonen , Lauri Viitasaari

We solve a physically significant extension of a classic problem in the theory of diffusion, namely the Ornstein-Uhlenbeck process [G. E. Ornstein and L. S. Uhlenbeck, Phys. Rev. 36, 823, (1930)]. Our generalised Ornstein-Uhlenbeck systems…

Statistical Mechanics · Physics 2009-11-11 V. Bezuglyy , B. Mehlig , M. Wilkinson , K. Nakamura , E. Arvedson

This paper studies the existence and global stability of generalized Ornstein-Uhlenbeck process for affine stochastic functional differential equations. Various very basic and important properties are established. In the applications, we…

Dynamical Systems · Mathematics 2025-08-14 Xiang Lv

We present a class of Gauss-Markov processes which can be represented as space-time scaled stationary Ornstein-Uhlenbeck processes defined on the real line. We give several explicit examples of the representation for certain Gauss bridge…

Probability · Mathematics 2019-01-28 Matyas Barczy , Peter Kern

Schr\"{o}dinger bridge is a stochastic optimal control problem to steer a given initial state density to another, subject to controlled diffusion and deadline constraints. A popular method to numerically solve the Schr\"{o}dinger bridge…

Optimization and Control · Mathematics 2023-09-14 Alexis M. H. Teter , Yongxin Chen , Abhishek Halder

Assuming that a threshold Ornstein-Uhlenbeck process is observed at discrete time instants, we propose generalized moment estimators to estimate the parameters. Our theoretical basis is the celebrated ergodic theorem. To use this theorem we…

Statistics Theory · Mathematics 2020-11-24 Yaozhong Hu , Yuejuan Xi

Spatio-temporal modelling is an increasingly popular topic in Statistics. Our paper contributes to this line of research by developing the theory, simulation and inference for a spatio-temporal Ornstein-Uhlenbeck process. We conduct…

Methodology · Statistics 2019-05-20 Michele Nguyen , Almut E. D. Veraart