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The G-Brownian-motion-driven stochastic differential equations (G-SDEs) as well as the G-expectation, which were seminally proposed by Peng and his colleagues, have been extensively applied to describing a particular kind of uncertainty…

Probability · Mathematics 2025-01-08 Xiaoxiao Peng , Shijie Zhou , Wei Lin , Xuerong Mao

Measure Differential Equations (MDE) describe the evolution of probability measures driven by probability velocity fields, i.e. probability measures on the tangent bundle. They are, on one side, a measure-theoretic generalization of…

Analysis of PDEs · Mathematics 2020-12-18 Fabio Camilli , Giulia Cavagnari , Raul De Maio , Benedetto Piccoli

We develop a unified PDE-probabilistic framework for pointwise gradient and Hessian estimates of Markov semigroups associated with stochastic differential equations with singular and unbounded coefficients. Under mild local structural…

Probability · Mathematics 2026-04-02 Pengcheng Xia , Longjie Xie , Xicheng Zhang

This paper introduces a new approach to generating sample paths of unknown Markovian stochastic differential equations (SDEs) using diffusion models, a class of generative AI methods commonly employed in image and video applications. Unlike…

Machine Learning · Computer Science 2026-03-17 Xuefeng Gao , Jiale Zha , Xun Yu Zhou

We show regularity properties of local densities of solutions of stochastic differential equations (SDEs) with the Fourier analytic approach. With this simple method, statements that were previously derived with approaches using Malliavin…

Probability · Mathematics 2025-05-01 Simon Ellinger

In this paper we mainly investigate the strong and weak well-posedness of a class of McKean-Vlasov stochastic (partial) differential equations. The main existence and uniqueness results state that we only need to impose some local…

Probability · Mathematics 2024-01-15 Wei Hong , Shanshan Hu , Wei Liu

There has been a great deal of recent interest in learning and approximation of functions that can be expressed as expectations of a given nonlinearity with respect to its random internal parameters. Examples of such representations include…

Optimization and Control · Mathematics 2022-12-05 Tanya Veeravalli , Maxim Raginsky

Stochastic differential equations (SDEs) are a staple of mathematical modelling of temporal dynamics. However, a fundamental limitation has been that such models have typically been relatively inflexible, which recent work introducing…

Machine Learning · Computer Science 2021-05-12 Patrick Kidger , James Foster , Xuechen Li , Harald Oberhauser , Terry Lyons

Many complex structures and stochastic patterns emerge from simple kinetic rules and local interactions, and are governed by scale invariance properties in combination with effects of the global geometry. We consider systems that can be…

Statistical Mechanics · Physics 2013-09-17 Adnan Ali , Robin C. Ball , Stefan Grosskinsky , Ellak Somfai

Let $X$ be a regular one-dimensional transient diffusion and $L^y$ be its local time at $y$. The stochastic differential equation (SDE) whose solution corresponds to the process $X$ conditioned on $[L^y_{\infty}=a]$ for a given $a\geq 0$ is…

Probability · Mathematics 2017-12-29 Umut Çetin

This paper is devoted to study the qualitative properties of hybrid measure differential equations (HMDEs, for short). We establish several results on the existence of global solutions, including the existence of regulated, continuous,…

Classical Analysis and ODEs · Mathematics 2023-01-02 Claudio A. Gallegos , Hernán R. Henríquez , Jaqueline G. Mesquita

We prove limit theorems for systems of interacting diffusions on sparse graphs. For example, we deduce a hydrodynamic limit and the propagation of chaos property for the stochastic Kuramoto model with interactions determined by…

Probability · Mathematics 2020-01-01 Roberto I. Oliveira , Guilherme H. Reis , Lucas M. Stolerman

Stochastic differential equation mixed-effects models (SDEMEMs) are flexible hierarchical models that are able to account for random variability inherent in the underlying time-dynamics, as well as the variability between experimental units…

Computation · Statistics 2021-01-22 Samuel Wiqvist , Andrew Golightly , Ashleigh T. McLean , Umberto Picchini

We study the numerical approximation of the invariant measure of a viscous scalar conservation law, one-dimensional and periodic in the space variable, and stochastically forced with a white-in-time but spatially correlated noise. The flux…

Analysis of PDEs · Mathematics 2021-05-27 Sébastien Boyaval , Sofiane Martel , Julien Reygner

We show existence of an infinitesimally invariant measure $m$ for a large class of divergence and non-divergence form elliptic second order partial differential operators with locally Sobolev regular diffusion coefficient and drift of some…

Probability · Mathematics 2022-01-21 Haesung Lee , Gerald Trutnau

In this paper we study macroscopic density equations in which the diffusion coefficient depends on a weighted spatial average of the density itself. We show that large differences (not present in the local density-dependence case) appear…

Statistical Mechanics · Physics 2009-11-11 Cristobal Lopez

Stochastic differential equations (SDEs) are of utmost importance in various scientific and industrial areas. They are the natural description of dynamical processes whose precise equations of motion are either not known or too expensive to…

Methodology · Statistics 2017-11-08 Philipp Frank , Theo Steininger , Torsten A. Enßlin

We study a local data inverse problem for the time-dependent Convection-Diffusion Equation (CDE) in a bounded domain where a part of the boundary is treated to be inaccessible. Up on assuming the inaccessible part to be flat, we seek for…

Analysis of PDEs · Mathematics 2025-01-09 Pranav Kumar , Anamika Purohit

We consider a mean-field system of path-dependent stochastic interacting diffusions in random media over a finite time window. The interaction term is given as a function of the empirical measure and is allowed to be non-linear and path…

Probability · Mathematics 2022-03-03 Rangel Baldasso , Alan Pereira , Guilherme Reis

We study the ergodic properties of finite-dimensional systems of SDEs driven by non-degenerate additive fractional Brownian motion with arbitrary Hurst parameter $H\in(0,1)$. A general framework is constructed to make precise the notions of…

Probability · Mathematics 2007-05-23 Martin Hairer
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