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We introduce a family of stochastic models motivated by the study of nonequilibrium steady states of fluid equations. These models decompose the deterministic dynamics of interest into fundamental building blocks, i.e., minimal vector…

Probability · Mathematics 2025-05-07 Andrea Agazzi , Jonathan C. Mattingly , Omar Melikechi

Mainstream flow matching methods typically focus on learning the local velocity field, which inherently requires multiple integration steps during generation. In contrast, Mean Velocity Flow models establish a relationship between the local…

Machine Learning · Computer Science 2026-03-18 Chenrui Ma

Flow Matching (FM) is a recent generative modelling technique: we aim to learn how to sample from distribution $\mathfrak{X}_1$ by flowing samples from some distribution $\mathfrak{X}_0$ that is easy to sample from. The key trick is that…

Differential Geometry · Mathematics 2025-10-24 Finn M. Sherry , Bart M. N. Smets

Consider a continuous-state branching population constructed as a flow of nested subordinators. Inverting the subordinators and reversing time give rise to a flow of coalescing Markov processes (with negative jumps) which correspond to the…

Probability · Mathematics 2018-12-04 Clément Foucart , Chunhua Ma , Bastien Mallein

The flow of a two--layer stratified fluid over an abrupt topographic obstacle, simulating relevant situations in oceanographic problems, is investigated numerically and experimentally in a simplified two--dimensional situation. Experimental…

Fluid Dynamics · Physics 2008-10-02 C. Cabeza , J. Varela , I. Bove , D. Freire , Arturo C. Marti , L. G. Sarasua , G. Usera , R. Montagne , M. Araujo

Let G be a topological compact group acting on some space Y. We study a decomposition of Y-indexed stochastic processes, based on the orthogonality relations between the characters of the irreducible representations of G. In the particular…

Probability · Mathematics 2007-05-23 Giovanni Peccati , Jean-Renaud Pycke

Bridge functions, the missing link in the exact description of strong correlations, are indirectly extracted from specially designed molecular dynamics simulations of classical one-component plasma liquids and accurately parameterized.…

Plasma Physics · Physics 2022-06-14 F. Lucco Castello , P. Tolias , T. Dornheim

The purpose of this paper is to bridge kinetic plasma descriptions and low frequency single fluid models. More specifically, the asymptotics leading to Magneto-Hydro-Dynamic (MHD) regimes starting from the Vlasov-Maxwell system are…

Plasma Physics · Physics 2020-04-21 A. Crestetto , F. Deluzet , D. Doyen

A fluid queue is a stochastic process which moves linearly with a rate that is determined by the state of a continuous-time Markov chain (CTMC). In this paper we construct an approximation to a fluid queue using a quasi birth-and-death…

Probability · Mathematics 2025-04-25 Nigel Bean , Angus Lewis

We propose a novel stochastic method to exactly generate Brownian paths conditioned to start at an initial point and end at a given final point during a fixed time $t_{f}$. These paths are weighted with a probability given by the overdamped…

Statistical Mechanics · Physics 2015-05-14 Satya N. Majumdar , Henri Orland

We consider the vacuum partition function of a 4d scalar QFT in a curved background as function of bare marginal and relevant couplings. A local UV cutoff $\Lambda(x)$ transforming under Weyl rescalings allows to construct Weyl invariant…

High Energy Physics - Theory · Physics 2022-01-19 Ulrich Ellwanger

We study a one-parameter family of countably piecewise linear interval maps, which, although Markov, fail the `large image property'. This leads to conservative as well as dissipative behaviour for different maps in the family with respect…

Dynamical Systems · Mathematics 2019-11-25 Henk Bruin , Mike Todd

Consider N particles moving independently, each one according to a subcritical continuous-time Galton-Watson process unless it hits 0, at which time it jumps instantaneously to the position of one of the other particles chosen uniformly at…

Probability · Mathematics 2012-06-28 Amine Asselah , Pablo A. Ferrari , Pablo Groisman , Matthieu Jonckheere

In this paper our first goal is to give precise definition of the L\'evy bridges with random length. Our second task is to establish the Markov property of this process with respect to its completed natural filtration and thus with respect…

Probability · Mathematics 2019-06-03 Mohamed Erraoui , Astrid Hilbert , Mohammed Louriki

Non-Newtonian fluid flow might be driven by spatially nonlocal velocity, the dynamics of which can be described by promising fractional derivative models. This short communication proposes a space FrActional-order Constitutive Equation…

Fluid Dynamics · Physics 2016-12-13 HongGuang Sun , Yong Zhang , Song Wei , Jianting Zhu

We consider a stochastic flow on $\mathds{R}$ generated by an SDE with its drift being a function of bounded variation. We show that the flow is differentiable with respect to the initial conditions. Asymptotic properties of the flow are…

Probability · Mathematics 2014-04-10 Olga V. Aryasova , Andrey Yu. Pilipenko

Flow matching and diffusion bridge models have emerged as leading paradigms in generative speech enhancement, modeling stochastic processes between paired noisy and clean speech signals based on principles such as flow matching, score…

Audio and Speech Processing · Electrical Eng. & Systems 2026-02-23 Dahan Wang , Jun Gao , Tong Lei , Yuxiang Hu , Changbao Zhu , Kai Chen , Jing Lu

This paper provides a formulation of the log-homotopy particle flow from the perspective of variational inference. We show that the transient density used to derive the particle flow follows a time-scaled trajectory of the Fisher-Rao…

Machine Learning · Statistics 2026-03-06 Yinzhuang Yi , Jorge Cortés , Nikolay Atanasov

The Fleming-Viot process with parent-independent mutation process is one particular neutral population genetic model. As time goes by, some initial species are replaced by mutated ones gradually. Once the population mutation rate is high,…

Probability · Mathematics 2016-03-16 Youzhou Zhou

This work deals with the investigation of bifurcating fluid phenomena using a reduced order modelling setting aided by artificial neural networks. We discuss the POD-NN approach dealing with non-smooth solutions set of nonlinear…

Fluid Dynamics · Physics 2023-08-08 Federico Pichi , Francesco Ballarin , Gianluigi Rozza , Jan S. Hesthaven
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