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The $L^k$-Wasserstein distance $\mathbb{W}_k (k\ge 1)$ and the probability distance $\mathbb{W}_\psi$ induced by a concave function $\psi$, are estimated between different diffusion processes with singular coefficients. As applications, the…

Probability · Mathematics 2023-11-07 Xing Huang , Panpan Ren , Feng-Yu Wang

We derive the Fokker-Planck equation on the parametric space. It is the Wasserstein gradient flow of relative entropy on the statistical manifold. We pull back the PDE to a finite dimensional ODE on parameter space. Some analytical example…

Optimization and Control · Mathematics 2020-06-16 Wuchen Li , Shu Liu , Hongyuan Zha , Haomin Zhou

Probabilistic tractography based on diffusion weighted MRI has become a powerful approach for quantifying structural brain connectivities. In several works the similarity of probabilistic tractography and path integrals was already pointed…

Analysis of PDEs · Mathematics 2015-02-25 Marco Reisert

We develop a theory of optimal transport for stationary random measures with a focus on stationary point processes and construct a family of distances on the set of stationary random measures. These induce a natural notion of interpolation…

Probability · Mathematics 2024-02-02 Matthias Erbar , Martin Huesmann , Jonas Jalowy , Bastian Müller

This study investigates the first passage time (FPT) properties of particles with a broad class of positive stochastic diffusion coefficients (DCs), representing diffusion in heterogeneous environments or of particles with conformational…

Statistical Mechanics · Physics 2026-05-18 Go Uchida , Hiromi Miyoshi , Hitoshi Washizu

This paper introduces a comprehensive extension of the path integral formalism to model stochastic processes with arbitrary multiplicative noise. To do so, It\^o diffusive process is generalized by incorporating a multiplicative noise term…

Mathematical Physics · Physics 2025-03-06 F. S. Abril-Bermúdez , C. J. Quimbay , J. E. Trinidad-Segovia , M. A Sánchez-Granero

This paper studies time-inhomogeneous nonequilibrium diffusion processes, including both Brownian dynamics and Langevin dynamics. We derive upper bounds of the relative entropy production of the time-inhomogeneous process with respect to…

Probability · Mathematics 2021-04-20 Wei Zhang

We investigate a Poisson-Nernst-Planck type system in three spatial dimensions where the strength of the electric drift depends on a possibly small parameter and the particles are assumed to diffuse quadratically. On grounds of the global…

Analysis of PDEs · Mathematics 2015-10-23 Jonathan Zinsl

In the case of diffusions on $\mathbb R^d$ with constant diffusion matrix, without assuming reversibility nor hypoellipticity, we prove that the contractivity of the deterministic drift is equivalent to the constant rate contraction of…

Probability · Mathematics 2023-04-06 Pierre Monmarché

Assuming that a reflected Ornstein-Uhlenbeck state process is observed at discrete time instants, we propose generalized moment estimators to estimate all drift and diffusion parameters via the celebrated ergodic theorem. With the sampling…

Statistics Theory · Mathematics 2020-09-14 Yaozhong Hu , Yuejuan Xi

Mathematical models based on probability density functions (PDF) have been extensively used in hydrology and subsurface flow problems, to describe the uncertainty in porous media properties (e.g., permeability modelled as random field).…

Fluid Dynamics · Physics 2020-06-01 Matteo Icardi , Marco Dentz

Score-based diffusion models have proven effective in image generation and have gained widespread usage; however, the underlying factors contributing to the performance disparity between stochastic and deterministic (i.e., the probability…

Machine Learning · Computer Science 2024-03-19 Yuji Hirono , Akinori Tanaka , Kenji Fukushima

We study the problem of estimating a sequence of evolving probability distributions from historical data, where the underlying distribution changes over time in a nonstationary and nonparametric manner. To capture gradual changes, we…

Optimization and Control · Mathematics 2025-12-16 Edward J. Anderson , Dominic S. T. Keehan

Based on the continuous time random walk, we derive the Fokker-Planck equations with Caputo-Fabrizio fractional derivative, which can effectively model a variety of physical phenomena, especially, the material heterogeneities and structures…

Numerical Analysis · Mathematics 2020-08-24 Minghua Chen , Jiankang Shi , Weihua Deng

The diffusive transport distance, a novel pseudo-metric between probability measures on the real line, is introduced. It generalizes Martingale optimal transport, and forms a hierarchy with the Hellinger and the Wasserstein metrics. We…

Analysis of PDEs · Mathematics 2025-01-27 Daniel Matthes , Eva-Maria Rott , André Schlichting

Fokker-Planck equation with the velocity-dependent coefficients is considered for various isotropic systems on the basis of probability transition (PT) approach. This method provides the self-consistent and universal description of friction…

Plasma Physics · Physics 2009-11-07 S. A. Trigger

Starting from a Langevin description of active particles that move with constant speed in infinite two-dimensional space and its corresponding Fokker-Planck equation, we develop a systematic method that allows us to obtain the…

Statistical Mechanics · Physics 2014-05-06 Francisco J. Sevilla , Luis A. Gomez Nava

In this paper, we consider the density estimation problem associated with the stationary measure of ergodic It\^o diffusions from a discrete-time series that approximate the solutions of the stochastic differential equations. To take an…

Numerical Analysis · Mathematics 2021-09-10 Yiqi Gu , John Harlim , Senwei Liang , Haizhao Yang

Although an intimate relation between entropy and diffusion has been advocated for many years and even seems to have been verified in theory and experiments, a quantitatively reliable study, and any derivation of an algebraic relation…

Statistical Mechanics · Physics 2020-07-22 Subhajit Acharya , Biman Bagchi

For a fixed $T$ and $k \geq 2$, a $k$-dimensional vector stochastic differential equation $dX_t=\mu(X_t, \theta)dt+\nu(X_t)dW_t,$ is studied over a time interval $[0,T]$. Vector of drift parameters $\theta$ is unknown. The dependence in…

Statistics Theory · Mathematics 2023-07-19 Miljenko Huzak , Snježana Lubura Strunjak , Andreja Vlahek Štrok