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In this article we consider likelihood-based estimation of static parameters for a class of partially observed McKean-Vlasov (POMV) diffusion process with discrete-time observations over a fixed time interval. In particular, using the…

Methodology · Statistics 2024-11-12 Ajay Jasra , Mohamed Maama , Raul Tempone

From the observation of a diffusion path $(X_t)_{t\in [0,T]}$ on a compact connected $d$-dimensional manifold $\mathcal{M}$ without boundary, we consider the problem of estimating the stationary measure $\mu$ of the process. Wang and Zhu…

Statistics Theory · Mathematics 2026-01-12 Vincent Divol , Hélène Guérin , Dinh-Toan Nguyen , Viet Chi Tran

This paper derives the Fokker-Planck (FP) equation for a particle moving in potential by a randomly modulated dipole. The FP equation describes the anomalous diffusion observed in the companion paper [1] and breaks the conservation of the…

Mathematical Physics · Physics 2022-05-03 S. Katagiri , Y. Matsuo , Y. Matsuoka , A. Sugamoto

The entropy production rate is a central quantity in non-equilibrium statistical physics, scoring how far a stochastic process is from being time-reversible. In this paper, we compute the entropy production of diffusion processes at…

Statistical Mechanics · Physics 2023-06-19 Lancelot Da Costa , Grigorios A. Pavliotis

We propose a general method to identify nonlinear Fokker--Planck--Kolmogorov equations (FPK equations) as gradient flows on the space of probability measures on $\mathbb{R}^d$ with a natural differential geometry. Our notion of gradient…

Analysis of PDEs · Mathematics 2024-11-11 Marco Rehmeier , Michael Röckner

We derive the hydrodynamic limit of a kinetic equation where the interactions in velocity are modelled by a linear operator (Fokker-Planck or Linear Boltzmann) and the force in the Vlasov term is a stochastic process with high amplitude and…

Analysis of PDEs · Mathematics 2020-03-23 Arnaud Debussche , Julien Vovelle

We discuss a relativistic diffusion in the proper time in an approach of Schay and Dudley. We derive (Langevin) stochastic differential equations in various coordinates.We show that in some coordinates the stochastic differential equations…

High Energy Physics - Theory · Physics 2009-11-13 Z. Haba

The exponential contraction in $L^1$-Wasserstein distance and exponential convergence in $L^q$-Wasserstein distance ($q\geq 1$) are considered for stochastic differential equations with irregular drift. When the irregular drift drift is…

Probability · Mathematics 2024-04-22 Shao-Qin Zhang

Realistic models of biological processes typically involve interacting components on multiple scales, driven by changing environment and inherent stochasticity. Such models are often analytically and numerically intractable. We revisit a…

Populations and Evolution · Quantitative Biology 2022-01-19 K. Bodova , E. Szep , N. H. Barton

We present a simple approach to study the one-dimensional pressureless Euler system via adhesion dynamics in the Wasserstein space of probability measures with finite quadratic moments. Starting from a discrete system of a finite number of…

Analysis of PDEs · Mathematics 2014-09-16 Luca Natile , Giuseppe Savaré

In the context of non-convex optimization, we let the temperature of a Langevin diffusion to depend on the diffusion's own density function. The rationale is that the induced density captures to some extent the landscape imposed by the…

Optimization and Control · Mathematics 2025-08-22 Yu-Jui Huang , Zachariah Malik

In this paper we consider a nonlinear Fokker-Planck equation with asymptotically small parameters. It describes the diffusion of finite-size particles in the presence of a fixed distribution of obstacles in the limit of low-volume fraction.…

Analysis of PDEs · Mathematics 2018-06-04 Maria Bruna , Martin Burger , Helene Ranetbauer , Marie-Therese Wolfram

We present a way to use Stein's method in order to bound the Wasserstein distance of order $2$ between two measures $\nu$ and $\mu$ supported on $\mathbb{R}^d$ such that $\mu$ is the reversible measure of a diffusion process. In order to…

Probability · Mathematics 2018-06-25 Thomas Bonis

In this paper we investigate the numerical approximation of an analogue of the Wasserstein distance for optimal transport on graphs that is defined via a discrete modification of the Benamou--Brenier formula. This approach involves the…

Numerical Analysis · Mathematics 2017-07-24 Matthias Erbar , Martin Rumpf , Bernhard Schmitzer , Stefan Simon

In parallel with advances in microscale imaging techniques, the fields of biology and materials science have focused on precisely extracting particle properties based on their diffusion behavior. Although the majority of real-world…

Mesoscale and Nanoscale Physics · Physics 2024-05-22 Kaito Takanami , Daisuke Taniguchi , Sawako Enoki , Masafumi Kuroda , Yasushi Okada , Yoshiyuki Kabashima

Context. Spacecraft observations have motivated the need for a refined description of the phase-space distribution function. Of particular importance is the pitch-angle diffusion coefficient that occurs in the Fokker-Planck transport…

High Energy Astrophysical Phenomena · Physics 2014-10-27 R. C. Tautz , A. Dosch , F. Effenberger , H. Fichtner , A. Kopp

In this paper, we provide the $O(\epsilon)$ corrections to the hydrodynamic model derived by Degond and Motsch from a kinetic version of the model by Vicsek & coauthors describing flocking biological agents. The parameter $\epsilon$ stands…

Mathematical Physics · Physics 2014-04-08 Pierre Degond , Tong Yang

We study normal diffusive and subdiffusive processes in a harmonic potential (Ornstein-Uhlenbeck process) on a uniformly growing/contracting domain. Our starting point is a recently derived fractional Fokker-Planck equation, which covers…

Statistical Mechanics · Physics 2019-07-31 F. Le Vot , S. B. Yuste , E. Abad

The dissipation of general convex entropies for continuous time Markov processes can be described in terms of backward martingales with respect to the tail filtration. The relative entropy is the expected value of a backward submartingale.…

Probability · Mathematics 2015-01-27 Joaquin Fontbona , Benjamin Jourdain

Score-based generative modeling with probability flow ordinary differential equations (ODEs) has achieved remarkable success in a variety of applications. While various fast ODE-based samplers have been proposed in the literature and…

Machine Learning · Statistics 2025-08-12 Xuefeng Gao , Lingjiong Zhu
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