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Related papers: Noise Inference For Ergodic L\'evy Driven SDE

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We study the ergodic behaviour of the McKean-Vlasov equations driven by common, divergence-free transport noise. In particular, we show that in dimension $d\geq 2$, if the noise is mixing and sufficiently strong it can enforce the…

Probability · Mathematics 2026-01-30 Benjamin Gess , Rishabh S. Gvalani , Adrian Martini

Modelling extreme events and heavy-tailed phenomena is central to building reliable predictive systems in domains such as finance, climate science, and safety-critical AI. While L\'evy processes provide a natural mathematical framework for…

Machine Learning · Computer Science 2026-05-12 Yaman Kindap , Manfred Opper , Benjamin Dupuis , Umut Simsekli , Tolga Birdal

We investigate synchronization by noise for stochastic differential equations (SDEs) driven by a fractional Brownian motion (fbm) with Hurst index $H\in(0,1)$. Provided that the SDE has a negative top Lyapunov exponent, we show that a weak…

Probability · Mathematics 2026-03-16 Alexandra Blessing , Mazyar Ghani Varzaneh

We develop a theory of ergodicity for a class of random dynamical systems where the driving noise is not white. The two main tools of our analysis are the strong Feller property and topological irreducibility, introduced in this work for a…

Probability · Mathematics 2011-11-09 M. Hairer , A. Ohashi

The aim of this paper is to develop estimation and inference methods for the drift parameters of multivariate L\'evy-driven continuous-time autoregressive processes of order $p\in\mathbb{N}$. Starting from a continuous-time observation of…

Methodology · Statistics 2023-07-26 Lorenzo Lucchese , Mikko S. Pakkanen , Almut E. D. Veraart

This paper is devoted to the study of an averaging principle for fractional stochastic differential equations in Rnwith L\'evy motion, using an integral transform method. We obtain a time-averaged equation under suitable assumptions.…

Probability · Mathematics 2020-04-21 Wenjing Xu , Jinqiao Duan , Wei Xu

In this article, we examine a stochastic partial differential equation (SPDE) driven by a symmetric $\alpha$-stable (S$\alpha$S) L\'evy noise, that is multiplied by a linear function $\sigma(u)=u$ of the solution. The solution is…

Probability · Mathematics 2024-09-20 Raluca M. Balan , Juan J. Jiménez

In this paper we study an Ergodic Markovian BSDE involving a forward process $X$ that solves an infinite dimensional forward stochastic evolution equation with multiplicative and possibly degenerate diffusion coefficient. A concavity…

Optimization and Control · Mathematics 2019-10-14 G. Guatteri , G. Tessitore

This study aims to analyze the ergodicity for stochastic 2D Boussinesq equations and explore the impact of a highly degenerate pure jump Levy noise acting only in the temperature equation, this noise could appear on a few Fourier modes. By…

Probability · Mathematics 2025-03-25 Jianhua Huang , Xuhui Peng , Xue Wang , Jiangwei Zhang

Diffusion with stochastic transport is investigated here when the random driving process is a very general Gaussian process, including Fractional Brownian motion. The purpose is the comparison with a deterministic PDE, which in certain…

Probability · Mathematics 2026-04-20 Franco Flandoli , Francesco Russo

We study strong approximation of scalar additive noise driven stochastic differential equations (SDEs) at time point $1$ in the case that the drift coefficient is bounded and has Sobolev regularity $s\in(0,1)$. Recently, it has been shown…

Probability · Mathematics 2024-03-14 Simon Ellinger , Thomas Müller-Gronbach , Larisa Yaroslavtseva

We study a multidimensional stochastic differential equation with additive noise: \[ d X_t=b(t, X_t) dt +d \xi_t, \] where the drift $b$ is integrable in space and time, and $\xi$ is either a fractional Brownian motion or a L\'evy process.…

Probability · Mathematics 2026-02-11 Oleg Butkovsky , Samuel Gallay

The asymptotic analysis of a class of stochastic partial differential equations (SPDEs) with fully locally monotone coefficients covering a large variety of physical systems, a wide class of quasilinear SPDEs and a good number of fluid…

Probability · Mathematics 2022-12-13 Ankit Kumar , Manil T. Mohan

We show that, in one spatial and arbitrary jump dimension, the averaged solution of a Marcustype SPDE with pure jump L\'evy transport noise satisfies a dissipative deterministic equation involving a fractional Laplace-type operator. To this…

Probability · Mathematics 2024-02-14 Franco Flandoli , Andrea Papini , Marco Rehmeier

We extend our recently introduced stochastic nonlocal traffic flow model to more general random perturbations, including Markovian noise derived from a discretized Jacobi-type stochastic differential equation. Invoking a deterministic…

Numerical Analysis · Mathematics 2026-03-26 Timo Böhme , Simone Göttlich , Andreas Neuenkirch

One-dimensional stochastic differential equations with additive L\'evy noise are considered. Conditions for existence and uniqueness of a strong solution are obtained. In particular, if the noise is a L\'evy symmetric stable process with…

Probability · Mathematics 2013-06-04 Andrey Pilipenko

We study the ergodic properties of a class of controlled stochastic differential equations (SDEs) driven by $\alpha$-stable processes which arise as the limiting equations of multiclass queueing models in the Halfin-Whitt regime that have…

Probability · Mathematics 2019-07-22 Ari Arapostathis , Hassan Hmedi , Guodong Pang , Nikola Sandrić

Literature is full of inference techniques developed to estimate the parameters of stochastic dynamical systems driven by the well-known Brownian noise. Such diffusion models are often inappropriate models to properly describe the dynamics…

Dynamical Systems · Mathematics 2024-02-19 Babak M. S. Arani

In this paper, we establish a moderate deviation principle for stochastic models of two-dimensional second grade fluids driven by L\'evy noise. We will adopt the weak convergence approach. Because of the appearance of jumps, this result is…

Probability · Mathematics 2018-01-26 Wuting Zheng , Jianliang Zhai , Tusheng Zhang

In this article, we employ a collection of stochastic differential equations with drift and diffusion coefficients approximated by neural networks to predict the trend of chaotic time series which has big jump properties. Our contributions…

Machine Learning · Computer Science 2022-11-04 Luxuan Yang , Ting Gao , Yubin Lu , Jinqiao Duan , Tao Liu
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