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We establish an existence result of a solution to a class of probability measure-valued equations, whose solutions can be associated with stationary distributions of many McKean-Vlasov diffusions with gradient-type drifts. Coefficients of…

Probability · Mathematics 2025-04-15 Shao-Qin Zhang

We prove global Sobolev regularity and pointwise upper bounds for the gradient of transition densities associated with second order differential operators in $\mathbb{R}^d$ with unbounded diffusion, drift and potential terms.

Analysis of PDEs · Mathematics 2022-10-03 Markus Kunze , Marianna Porfido , Abdelaziz Rhandi

We prove concentration inequalities and associated PAC bounds for continuous- and discrete-time additive functionals for possibly unbounded functions of multivariate, nonreversible diffusion processes. Our analysis relies on an approach via…

Probability · Mathematics 2024-10-15 Cathrine Aeckerle-Willems , Claudia Strauch , Lukas Trottner

We formulate a trajectorial version of the relative entropy dissipation identity for McKean$-$Vlasov diffusions, extending the results of the papers [FJ16,KST20a], which apply to non-interacting diffusions. Our stochastic analysis approach…

Probability · Mathematics 2021-05-27 Bertram Tschiderer , Lane Chun Yeung

In this paper we introduce some recent progresses on the convergence rate in Wasserstein distance for empirical measures of Markov processes. For diffusion processes on compact manifolds possibly with reflecting or killing boundary…

Probability · Mathematics 2025-07-22 Feng-Yu Wang

By using the spectrum of the underlying symmetric diffusion operator, the convergence in $L^p$-Wasserstein distance $\mathbb W_p (p\ge 1)$ is characterized for the empirical measure $\mu_t$ of non-symmetric subordinated diffusion processes…

Probability · Mathematics 2023-02-28 Feng-Yu Wang

For general absorbed Markov processes $(X_t)_{0\leq t<\tau_{\partial}}$ having a quasi-stationary distribution (QSD) $\pi$ and absorption time $\tau_{\partial}$, we introduce a Dobrushin-type criterion providing for exponential convergence…

Probability · Mathematics 2022-10-26 Oliver Tough

We characterize lower bounds for the Bakry-Emery Ricci tensor of nonsymmetric diffusion operators by convexity of entropy on the $L^2$-Wasserstein space, and define a curvature-dimension condition for general metric measure spaces together…

Differential Geometry · Mathematics 2017-02-10 Christian Ketterer

Motivated by queues with many servers, we study Brownian steady-state approximations for continuous time Markov chains (CTMCs). Our approximations are based on diffusion models (rather than a diffusion limit) whose steady-state, we prove,…

Probability · Mathematics 2014-09-12 Itai Gurvich

This paper is a natural continuation of \cite{Kr_20_2} and \cite{Kr_21_1} where strong Markov processes are constructed in time inhomogeneous setting with Borel measurable uniformly bounded and uniformly nondegenerate diffusion and drift in…

Probability · Mathematics 2021-02-24 N. V. Krylov

The paper presents a generalization of the local limit theorem on the convergence of inhomogeneous Markov chains to the diffusion limit for the case where the corresponding process coefficients satisfy weak regularity conditions and…

Probability · Mathematics 2025-06-02 I. Bitter , V. Konakov

In this paper, we provide bounds in Wasserstein and total variation distances between the distributions of the successive iterates of two functional autoregressive processes with isotropic Gaussian noise of the form $Y_{k+1} =…

Probability · Mathematics 2023-11-30 Alain Durmus , Andreas Eberle , Aurélien Enfroy , Arnaud Guillin , Pierre Monmarché

Continuous diffusion models have demonstrated remarkable performance in data generation across various domains, yet their efficiency remains constrained by two critical limitations: (1) the local adjacency structure of the forward Markov…

Machine Learning · Statistics 2025-05-29 Xunpeng Huang , Yingyu Lin , Nikki Lijing Kuang , Hanze Dong , Difan Zou , Yian Ma , Tong Zhang

In this paper we study the transition density and exponential ergodicity in total variation for an affine process on the canonical state space $\mathbb{R}_{\geq0}^{m}\times\mathbb{R}^{n}$. Under a H\"ormander-type condition for diffusion…

Probability · Mathematics 2020-06-18 Martin Friesen , Peng Jin , Jonas Kremer , Barbara Rüdiger

We generalize leading-order asymptotics of a form of the heat content of a submanifold (van den Berg & Gilkey 2015) to the setting of time-dependent diffusion processes in the limit of vanishing diffusivity. Such diffusion processes arise…

Analysis of PDEs · Mathematics 2021-03-22 Nathanael Schillling , Daniel Karrasch , Oliver Junge

We study a twice-differentiable transformation applied to a CKLS-type short-rate model with linear drift and power-type diffusion. The transformation yields a new process whose diffusion component has a square-root structure and whose drift…

Probability · Mathematics 2025-12-16 Boyuan Ning , Yasutaka Shimizu

Non-linear Hawkes processes with memory kernels given by the sum of Erlang kernels are considered. It is shown that their stability properties can be studied in terms of an associated class of piecewise deterministic Markov processes,…

Probability · Mathematics 2018-11-27 Aline Duarte , Eva Löcherbach , Guilherme Ost

We exhibit a large class of Lyapunov functionals for nonlinear drift-diffusion equations with non-homogeneous Dirichlet boundary conditions. These are generalizations of large deviation functionals for underlying stochastic many-particle…

Analysis of PDEs · Mathematics 2015-06-16 T. Bodineau , J. L. Lebowitz , C. Mouhot , C. Villani

In this paper, we study the asymptotic behavior of a fully-coupled slow-fast McKean-Vlasov stochastic system. Using the non-linear Poisson equation on Wasserstein space, we first establish the strong convergence in the averaging principle…

Probability · Mathematics 2022-07-14 Yun Li , Longjie Xie

We derive sharp, local and dimension dependent hypercontractive bounds on the Markov kernel of a large class of diffusion semigroups. Unlike the dimension free ones, they capture refined properties of Markov kernels, such as trace…

Probability · Mathematics 2013-09-19 Dominique Bakry , François Bolley , Ivan Gentil