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Related papers: Regularity and Sensitivity for McKean-Vlasov SPDEs

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The study of the density evolution naturally arises in Mean Field Game theory for the estimation of the density of the large population dynamics. In this paper, we study the density evolution of McKean-Vlasov stochastic differential…

Probability · Mathematics 2018-12-31 Peter E. Caines , Daniel Ho , Qingshuo Song

In this paper we study the randomized non-autonomous complete linear differential equation. The diffusion coefficient and the source term in the differential equation are assumed to be stochastic processes and the initial condition is…

Probability · Mathematics 2018-02-13 J. Catatayud , J. -C. Cortes , M. Jornet

This work focuses on the quantitative contraction rates for McKean-Vlasov stochastic differential equations (SDEs) with multiplicative noise. Under suitable conditions on the coefficients of the SDE, this paper derives explicit quantitative…

Probability · Mathematics 2025-09-30 Dan Noelck

This paper investigates neutral-type McKean-Vlasov stochastic differential equations in which the drift and diffusion coefficients depend on both the segment process and its distribution. Under a one-sided Lipschitz condition on the drift…

Probability · Mathematics 2025-11-25 Zhaohang Wang , Junhao Hu , Chenggui Yuan

We consider Mckean-Vlasov type stochastic differential equations with multiplicative noise arising from the random vortex method. Such an equation can be viewed as the mean-field limit of interacting particle systems with singular…

Probability · Mathematics 2024-04-09 Jiawei Li , Zhongmin Qian

In this paper we study the {\it pathwise stochastic Taylor expansion}, in the sense of our previous work \cite{Buckdahn_Ma_02}, for a class of It\^o-type random fields in which the diffusion part is allowed to contain both the random field…

Probability · Mathematics 2010-08-20 Rainer Buckdahn , Ingo Bulla , Jin Ma

We use an effective Markovian description to study the long-time behaviour of a nonlinear second order Langevin equation with Gaussian noise. When dissipation is neglected, the energy of the system grows as with time a power-law with an…

Chaotic Dynamics · Physics 2014-12-19 Kirone Mallick

Translational diffusion coefficients are routinely estimated from molecular dynamics simulations. Linear fits to mean squared displacement (MSD) curves have become the de facto standard, from simple liquids to complex biomacromolecules.…

Computational Physics · Physics 2020-11-20 Jakob Tómas Bullerjahn , Sören von Bülow , Gerhard Hummer

This paper gives direct derivations of the differential equations and likelihood formulas of diffusion models assuming only knowledge of Gaussian distributions. A VAE analysis derives both forward and backward stochastic differential…

Machine Learning · Computer Science 2023-03-07 David McAllester

In this paper, by introducing a new type asymptotic coupling by reflection, we explore the long time behavior of random probability measure flows associated with a large class of one-dimensional McKean-Vlasov SDEs with common noise.…

Probability · Mathematics 2024-01-17 Bao Jianhai , Wang Jian

We develop an explicit Milstein-type scheme for McKean-Vlasov stochastic differential equations using the notion of derivative with respect to measure introduced by Lions and discussed in \cite{cardaliaguet2013}. The drift coefficient is…

Probability · Mathematics 2022-02-08 Chaman Kumar , Neelima

In this article we show that a finite dimensional stochastic differential equation driven by a L\'evy process can be formulated as a stochastic partial differential equation. We prove the existence and uniqueness of strong solutions of such…

Probability · Mathematics 2018-02-15 Suprio Bhar , Rajeev Bhaskaran , Barun Sarkar

In this short note, we establish Malliavin differentiability of McKean-Vlasov Stochastic Differential Equations (MV-SDEs) with drifts satisfying both a locally Lipschitz and a one-sided Lipschitz assumption, and where the diffusion…

Probability · Mathematics 2025-05-09 Goncalo dos Reis , Zac Wilde

We consider sensitivity of a generic stochastic optimization problem to model uncertainty. We take a non-parametric approach and capture model uncertainty using Wasserstein balls around the postulated model. We provide explicit formulae for…

Optimization and Control · Mathematics 2022-01-19 Daniel Bartl , Samuel Drapeau , Jan Obloj , Johannes Wiesel

In this paper, we investigate an optimal control problem for McKean-Vlasov stochastic partial differential equations, in which the coefficients depend on the law of the state process. For systems with nonconvex control sets, we establish a…

Probability · Mathematics 2026-03-09 Liangying Chen , Wilhelm Stannat

This article is a continuation of our first work \cite{chaudruraynal:frikha}. We here establish some new quantitative estimates for propagation of chaos of non-linear stochastic differential equations in the sense of McKean-Vlasov. We…

Analysis of PDEs · Mathematics 2021-08-26 Noufel Frikha , Paul-Eric Chaudru de Raynal

As the limit equations of mean-field particle systems perturbed by common environmental noise, the McKean-Vlasov stochastic differential equations with common noise have received a lot of attention. Moreover, past dependence is an…

Probability · Mathematics 2025-02-18 Xing Chen , Xiaoyue Li , Chenggui Yuan

In this article we consider Bayesian estimation of static parameters for a class of partially observed McKean-Vlasov diffusion processes with discrete-time observations over a fixed time interval. This problem features several obstacles to…

Computation · Statistics 2025-04-23 Ajay Jasra , Amin Wu

Semilinear stochastic evolution equations with multiplicative L\'evy noise and monotone nonlinear drift are considered. Unlike other similar work we do not impose coercivity conditions on coefficients. Existence and uniqueness of the mild…

Probability · Mathematics 2013-12-03 Erfan Salavati , Bijan Z. Zangeneh

We establish results for the first sensitivity analysis of the stochastic fluid models (SFMs). We derive expressions for the sensitivity analysis of the key stationary and transient (time-dependent) quantities of this class of models. We…

Probability · Mathematics 2026-05-21 Anna Aksamit , Małgorzata M. O'Reilly , Zbigniew Palmowski
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