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Stochastic calculus with respect to fractional Brownian motion (fBm) has attracted a lot of interest in recent years, motivated in particular by applications in finance and Internet traffic modeling. Multifractional Brownian motion (mBm) is…

Probability · Mathematics 2011-03-29 Joachim Lebovits , Jacques Lévy Vehel

We consider the problem of estimating the roughness of the volatility process in a stochastic volatility model that arises as a nonlinear function of fractional Brownian motion with drift. To this end, we introduce a new estimator that…

Statistical Finance · Quantitative Finance 2026-04-17 Xiyue Han , Alexander Schied

Bayesian analyses combine information represented by different terms in a joint Bayesian model. When one or more of the terms is misspecified, it can be helpful to restrict the use of information from suspect model components to modify…

Methodology · Statistics 2022-06-27 Xuejun Yu , David J. Nott , Michael Stanley Smith

In this paper, we consider the stochastic %equations of incompressible non-Newtonian fluids driven by a cylindrical Wiener process $W$ with shear rate dependent on viscosity in a bounded Lipschitz domain $D\in \mathbb{R}^n$ during the time…

Analysis of PDEs · Mathematics 2017-01-06 Zhong Tan , Huaqiao Wang , Yucong Wang

We focus on variational inference in dynamical systems where the discrete time transition function (or evolution rule) is modelled by a Gaussian process. The dominant approach so far has been to use a factorised posterior distribution,…

Machine Learning · Statistics 2018-12-17 Alessandro Davide Ialongo , Mark van der Wilk , James Hensman , Carl Edward Rasmussen

We introduce the local martingale problem associated to semilinear stochastic evolution equations driven by a cylindrical Wiener process and establish a one-to-one correspondence between solutions of the martingale problem and…

Probability · Mathematics 2014-04-09 Markus C. Kunze

This work is devoted to the variational derivation of a reduced model for brittle membranes in finite elasticity. The main mathematical tools we develop for our analysis are: (i) a new density result in $GSBV^{p}$ of functions satisfying a…

Analysis of PDEs · Mathematics 2022-09-23 Stefano Almi , Dario Reggiani , Francesco Solombrino

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

We consider a broad class of semilinear SPDEs with multiplicative noise driven by a finite-dimensional Wiener process. We show that, provided that an infinite-dimensional analogue of H\"ormander's bracket condition holds, the Malliavin…

Probability · Mathematics 2019-11-11 Andris Gerasimovics , Martin Hairer

Classical density functional theory (DFT) provides an exact variational framework for determining the equilibrium properties of inhomogeneous fluids. We report a generalization of DFT to treat the non-equilibrium dynamics of classical…

Soft Condensed Matter · Physics 2013-09-06 Matthias Schmidt , Joseph M. Brader

The stochastic trajectories of molecules in living cells, as well as the dynamics in many other complex systems, often exhibit memory in their path over long periods of time. In addition, these systems can show dynamic heterogeneities due…

Statistical Mechanics · Physics 2024-07-10 Michał Balcerek , Agnieszka Wyłomańska , Krzysztof Burnecki , Ralf Metzler , Diego Krapf

The Wiener's path integral plays a central role in the studies of Brownian motion. Here we derive exact path-integral representations for the more general \emph{fractional} Brownian motion (fBm) and for its time derivative process -- the…

Statistical Mechanics · Physics 2022-12-28 Baruch Meerson , Olivier Bénichou , Gleb Oshanin

Assume that $X$ is a continuous square integrable process with zero mean, defined on some probability space $(\Omega,\mathrm {F},\mathrm {P})$. The classical characterization due to P. L\'{e}vy says that $X$ is a Brownian motion if and only…

Probability · Mathematics 2011-03-15 Yuliya Mishura , Esko Valkeila

We address a general optimal switching problem over finite horizon for a stochastic system described by a differential equation driven by Brownian motion. The main novelty is the fact that we allow for infinitely many modes (or regimes,…

Optimization and Control · Mathematics 2019-08-07 Marco Fuhrman , Marie-Amélie Morlais

By using a simple observation that the density processes appearing in Ito's martingale representation theorem are invariant under the change of measures, we establish a non-linear version of the Cameron-Martin formula for solutions of a…

Probability · Mathematics 2010-11-16 G. Liang , A. Lionnet , Z. Qian

Stochastic integration \textit{wrt} Gaussian processes has raised strong interest in recent years, motivated in particular by its applications in Internet traffic modeling, biomedicine and finance. The aim of this work is to define and…

Probability · Mathematics 2018-02-15 Joachim Lebovits

Let $(Z_t)_{t\geq 0}$ denote the derivative martingale of branching Brownian motion, i.e.\@ the derivative with respect to the inverse temperature of the normalized partition function at critical temperature. A well-known result by Lalley…

Probability · Mathematics 2018-06-20 Pascal Maillard , Michel Pain

We introduce a differential structure for the space of weakly geometric p rough paths over a Banach space V for 2<p<3. We begin by considering a certain natural family of smooth rough paths and differentiating in the truncated tensor…

Probability · Mathematics 2011-03-01 Zhongmin Qian , Jan Tudor

We discuss a family of time-inhomogeneous two-dimensional diffusions, defined over a finite time interval $[0,T]$, having transition density functions that are expressible in terms of the integral kernels for negative exponentials of the…

Probability · Mathematics 2023-07-04 Jeremy Clark , Barkat Mian

Path integrals developed by Richard Feynman have been an important tool in Physics in studying quantum field theory. In mathematics, it has also been widely used in providing formal proofs in the study of Index theorem and asymptotic…

Probability · Mathematics 2017-02-23 Zhehua Li