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In order to bring contraction analysis into the very fruitful and topical fields of stochastic and Bayesian systems, we extend here the theory describes in \cite{Lohmiller98} to random differential equations. We propose new definitions of…

Optimization and Control · Mathematics 2013-09-27 Nicolas Tabareau , Jean-Jacques Slotine

In this paper, we construct scaling limits of some branching random walks in random environment whose off-spring distributions have infinite variance. The Laplace functional of the obtained random measure is given by a non-linear PAM, whose…

Probability · Mathematics 2023-09-19 Ruhong Jin

We study the robustness of classifiers to various kinds of random noise models. In particular, we consider noise drawn uniformly from the $\ell\_p$ ball for $p \in [1, \infty]$ and Gaussian noise with an arbitrary covariance matrix. We…

Machine Learning · Computer Science 2018-06-25 Jean-Yves Franceschi , Alhussein Fawzi , Omar Fawzi

The Cahn-Hilliard/Allen-Cahn equation with noise is a simplified mean field model of stochastic microscopic dynamics associated with adsorption and desorption-spin flip mechanisms in the context of surface processes. For such an equation we…

Probability · Mathematics 2022-10-13 Dimitra C. Antonopoulou , Geogia Karali , Annie Millet

We consider exit problems for small white noise perturbations of a dynamical system generated by a vector field, and a domain containing a critical point with all positive eigenvalues of linearization. We prove that, in the vanishing noise…

Probability · Mathematics 2020-12-15 Yuri Bakhtin , Hong-Bin Chen

This paper presents a general approach to linear stochastic processes driven by various random noises. Mathematically, such processes are described by linear stochastic differential equations of arbitrary order (the simplest non-trivial…

Condensed Matter · Physics 2009-10-28 Alon Drory

We study the asymptotic probability that a random walk with heavy-tailed increments crosses a high boundary on a random time interval. We use new techniques to extend results of Asmussen [Ann. Appl. Probab. 8 (1998) 354-374] to completely…

Probability · Mathematics 2017-11-29 Sergey Foss , Zbigniew Palmowski , Stan Zachary

We consider stochastic partial differential equations on $\mathbb{R}^{d}, d\geq 1$, driven by a Gaussian noise white in time and colored in space, for which the pathwise uniqueness holds. By using the Skorokhod representation theorem we…

Probability · Mathematics 2007-05-23 K. Bahlali , M. Eddahbi , M. Mellouk

We consider the thermally activated escape of an overdamped Brownian particle over a potential barrier in the presence of periodic driving. A time-dependent path-integral formalism is developed which allows us to derive asymptotically exact…

Statistical Mechanics · Physics 2009-10-31 Jörg Lehmann , Peter Reimann , Peter Hänggi

Given a stochastic structure with a filtration $\mathbb{F}$, the class of all random times whose conditional distribution functions are differentiable with respect to some $\mathbb{F}$ adapted non decreasing processes is considered. The…

Probability · Mathematics 2013-12-20 Shiqi Song

Stochastic systems characterised by a random driving in a form of the general stable noise are considered. The particle experiences long rests due to the traps the density of which is position-dependent and obeys a power-law form attributed…

Statistical Mechanics · Physics 2016-07-06 Tomasz Srokowski

In this paper, we prove that separation occurs for the stationary Prandtl equation, in the case of adverse pressure gradient, for a large class of boundary data at $x=0$.We justify the Goldstein singularity: more precisely, we prove that…

Analysis of PDEs · Mathematics 2018-02-13 Anne-Laure Dalibard , Nader Masmoudi

In this paper, we aim to study the asymptotic behaviour for a class of McKean-Vlasov stochastic partial differential equations with slow and fast time-scales. Using the variational approach and classical Khasminskii time discretization, we…

Probability · Mathematics 2022-01-21 Wei Hong , Shihu Li , Wei Liu

In this work we study high probability bounds for stochastic subgradient methods under heavy tailed noise. In this setting the noise is only assumed to have finite variance as opposed to a sub-Gaussian distribution for which it is known…

Optimization and Control · Mathematics 2024-04-16 Daniela A. Parletta , Andrea Paudice , Massimiliano Pontil , Saverio Salzo

In this paper, we first investigate the well-posedness of a backward stochastic differential equation where the driver depends on the law of the solution conditioned to a common noise. Under standard assumptions, we show that existence and…

Probability · Mathematics 2022-09-29 Remi Moreau

An assumed density approximate likelihood is derived for a class of partially observed stochastic compartmental models which permit observational over-dispersion. This is achieved by treating time-varying reporting probabilities as latent…

Methodology · Statistics 2025-05-22 Michael Whitehouse

The existence of random attractors for singular stochastic partial differential equations (SPDE) perturbed by general additive noise is proven. The drift is assumed only to satisfy the standard assumptions of the variational approach to…

Probability · Mathematics 2011-11-02 Benjamin Gess

According to their strength, the tracing properties of a code can be categorized as frameproof, separating, IPP and TA. It is known that if the minimum distance of the code is larger than a certain threshold then the TA property implies the…

Information Theory · Computer Science 2021-03-04 Marcel Fernandez , Jorge Urroz

We consider a stochastic partial differential equation with two logarithmic nonlinearities, with two reflections at 1 and -1 and with a constraint of conservation of the space average. The equation, driven by the derivative in space of a…

Analysis of PDEs · Mathematics 2019-10-21 Arnaud Debussche , Ludovic Goudenège

We study the stochastic dynamics of a two-dimensional particle assuming that the components of its position are two coupled random-acceleration processes evolving in a confining parabolic potential and are the subjects of independent…

Statistical Mechanics · Physics 2026-01-13 Victor Dotsenko , Gleb Oshanin , Leonid Pastur , Pascal Viot
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