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To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables…

Artificial Intelligence · Computer Science 2009-03-09 Toby Walsh

We consider slow / fast systems where the slow system is driven by fractional Brownian motion with Hurst parameter $H>{1\over 2}$. We show that unlike in the case $H={1\over 2}$, convergence to the averaged solution takes place in…

Probability · Mathematics 2023-03-07 Martin Hairer , Xue-Mei Li

In this paper we prove, for small Hurst parameters, the higher order differentiability of a stochastic flow associated with a stochastic differential equation driven by an additive multi-dimensional fractional Brownian noise, where the…

Probability · Mathematics 2018-05-15 Oussama Amine , David R. Baños , Frank Proske

In this paper, we study a class of one-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H>\ff 1 2$. The drift term of the equation is locally Lipschitz and unbounded in the…

Probability · Mathematics 2019-01-01 Shao-Qin Zhang , Chenggui Yuan

An innovative extension of Geometric Brownian Motion model is developed by incorporating a weighting factor and a stochastic function modelled as a mixture of power and trigonometric functions. Simulations based on this Modified Brownian…

Pricing of Securities · Quantitative Finance 2015-07-09 Gurjeet Dhesi , Muhammad Bilal Shakeel , Ling Xiao

Fractional Brownian motion is a Gaussian stochastic process with stationary, long-time correlated increments and is frequently used to model anomalous diffusion processes. We study numerically fractional Brownian motion confined to a finite…

Statistical Mechanics · Physics 2019-03-22 T. Guggenberger , G. Pagnini , T. Vojta , R. Metzler

This work deals with the one-dimensional Stefan problem with a general time-dependent boundary condition at the fixed boundary. Stochastic solutions are obtained using discrete random walks, and the results are compared with analytic…

Analysis of PDEs · Mathematics 2023-02-06 M. Ogren

We derive a stochastic Gronwall lemma with suprema over the paths in the upper bound of the assumed affine-linear growth assumption. This allows applications to It\^o processes with coefficients which depend on earlier time points such as…

Probability · Mathematics 2022-06-03 Martin Hutzenthaler , Tuan Anh Nguyen

Transport phenomena are ubiquitous in nature and known to be important for various scientific domains. Examples can be found in physics, electrochemistry, heterogeneous catalysis, physiology, etc. To obtain new information about diffusive…

Probability · Mathematics 2007-05-23 Denis S. Grebenkov

We consider a mixed stochastic differential equation driven by possibly dependent fractional Brownian motion and Brownian motion. Under mild regularity assumptions on the coefficients, it is proved that the equation has a unique solution.

Probability · Mathematics 2011-11-09 Yuliya Mishura , Georgiy Shevchenko

In this paper we develop a new approach to stochastic evolution equations with an unbounded drift $A$ which is dependent on time and the underlying probability space in an adapted way. It is well-known that the semigroup approach to…

Probability · Mathematics 2014-02-28 Matthijs Pronk , Mark Veraar

Stochastic integration w.r.t. fractional Brownian motion (fBm) has raised strong interest in recent years, motivated in particular by applications in finance and Internet traffic modelling. Since fBm is not a semi-martingale, stochastic…

Probability · Mathematics 2013-05-03 Joachim Lebovits

We consider a random process as a solution of stochastic differential equations with dependence of the coefficients on small parameter $\varepsilon$ and we suppose that the drift coefficients of these equations are unbounded on the…

Probability · Mathematics 2023-12-15 Ivan H. Krykun

In this short note we provide an elementary proof that a certain type of nonuniform sequential Doeblin minorization condition implies non-uniform sequential "geometric" ergodicity. Using this result several limit theorems for inhomogeneous…

Probability · Mathematics 2025-10-20 Yeor Hafouta , Brenden Williams

We provide sufficient conditions on the coefficients of a stochastic functional differential equation with bounded memory driven by Brownian motion which guarantee existence and uniqueness of a maximal local and global strong solution for…

Probability · Mathematics 2009-11-20 Max-K. von Renesse , Michael Scheutzow

We study the numerical approximation of SDEs with singular drifts (including distributions) driven by a fractional Brownian motion. Under the Catellier-Gubinelli condition that imposes the regularity of the drift to be strictly greater than…

Probability · Mathematics 2024-12-02 Ludovic Goudenège , El Mehdi Haress , Alexandre Richard

Exact generalized stochastic representation of deterministic interaction between two dynamical (quantum or classical) systems is derived which helps when considering one of them to replace another by equivalent commutative ($c$-number…

Statistical Mechanics · Physics 2007-05-23 Yuriy E. Kuzovlev

We consider a system of multiscale stochastic differential equations whose slow component is drivenby a fractional Brownian motion with Hurst parameter H greater than 1/2. Under ergodic assumptions ensuring the applicability of the…

Probability · Mathematics 2025-12-10 Xue-Mei Li , Colin Piernot , Szymon Sobczak , Kexing Ying

Consider generalized adapted stochastic integrals with respect to independently scattered random measures with second moments. We use a decoupling technique, known as the "principle of conditioning", to study their stable convergence…

Probability · Mathematics 2007-05-23 Giovanni Peccati , Murad S. Taqqu

In this paper, we prove a mimicking theorem for stochastic processes with an additive Gaussian noise along with some entropy and transport type estimates. As an application of these results, we prove sharp quantitative propagation of chaos…

Probability · Mathematics 2024-05-15 Kevin Hu , Kavita Ramanan , William Salkeld