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In this paper we explain how the notion of ''weak Dirichlet process'' is the suitable generalization of the one of semimartingale with jumps. For such a process we provide a unique decomposition which is new also for semimartingales: in…

Probability · Mathematics 2022-07-04 Elena Bandini , Francesco Russo

In 1998, Bou\'e and Dupuis proved a variational representation for exponentials of bounded Wiener functionals. Since their proof involves arguments related to the weak convergence of probability measures, the boundedness of functionals…

Probability · Mathematics 2015-05-21 Yuu Hariya

We review several results related to the problem of a quantum particle in a random environment. In an introductory part, we recall how several functionals of the Brownian motion arise in the study of electronic transport in weakly…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alain Comtet , Jean Desbois , Christophe Texier

The paper deals with exponential functionals of the linear Brownian motion which arise in different contexts such as continuous time finance models and one-dimensional disordered models. We study some properties of these exponential…

Condensed Matter · Physics 2007-05-23 Alain Comtet , Cécile Monthus , Marc Yor

We introduce a new class of stochastic processes called fractional Wiener-Weierstrass bridges. They arise by applying the convolution from the construction of the classical, fractal Weierstrass functions to an underlying fractional Brownian…

Probability · Mathematics 2024-01-01 Alexander Schied , Zhenyuan Zhang

We develop a new paradigm for finding bifurcations of solutions of nonlinear problems, which is based on the detection of extreme values of new type of variational functional associated with the considering problem. The variational…

Analysis of PDEs · Mathematics 2014-11-11 Yavdat Il'yasov , Alexsandr Ivanov

A simple variational Lagrangian is proposed for the time development of an arbitrary density matrix, employing the "factorization" of the density. Only the "kinetic energy" appears in the Lagrangian. The formalism applies to pure and mixed…

Fluid Dynamics · Physics 2009-11-10 R. Englman , A. Yahalom

Variational Inference is a powerful tool in the Bayesian modeling toolkit, however, its effectiveness is determined by the expressivity of the utilized variational distributions in terms of their ability to match the true posterior…

Machine Learning · Statistics 2019-05-10 Artem Sobolev , Dmitry Vetrov

In this paper we derive novel change of variable formulas for stochastic integrals w.r.t. a time-changed Brownian motion where we assume that the time-change is a general increasing stochastic process with finitely many jumps in a bounded…

Probability · Mathematics 2024-07-04 Giulia Di Nunno , Hannes Haferkorn , Asma Khedher , Michèle Vanmaele

We show that an infinitesimal step of gradient flow can be used for defining a novel approach for computing gradients of physical observables with respect to action parameters. Compared to the commonly used perturbative expansion, this…

High Energy Physics - Lattice · Physics 2023-11-28 Simone Bacchio

This paper deals with the identification of the multivariate fractional Brownian motion, a recently developed extension of the fractional Brownian motion to the multivariate case. This process is a $p$-multivariate self-similar Gaussian…

Statistics Theory · Mathematics 2011-11-16 Pierre-Olivier Amblard , Jean-François Coeurjolly

When the limiting compensator of a sequence of martingales is continuous, we obtain a weak convergence theorem for the martingales; the limiting process can be written as a Brownian motion evaluated at the compensator and we find sufficient…

Probability · Mathematics 2024-01-22 Bruno Rémillard , Jean Vaillancourt

The martingale part in the semimartingale decomposition of a Brownian motion with respect to an enlargement of its filtration, is an anticipative mapping of the given Brownian motion. In analogy to optimal transport theory, we define causal…

Probability · Mathematics 2017-12-13 Beatrice Acciaio , Julio Backhoff Veraguas , Anastasiia Zalashko

In this paper, we present several path properties, simulations, inferences, and generalizations of the weighted sub-fractional Brownian motion. A primary focus is on the derivation of the covariance function $R_{f,b}(s,t)$ for the weighted…

Probability · Mathematics 2024-09-10 Ramirez-Gonzalez Jose Hermenegildo , Sun Ying

This paper considers the effect of least squares procedures for nearly unstable linear time series with strongly dependent innovations. Under a general framework and appropriate scaling, it is shown that ordinary least squares procedures…

Statistics Theory · Mathematics 2009-09-29 Boris Buchmann , Ngai Hang Chan

In this article, we will first introduce a class of Gaussian processes, and prove the quasi-invariant theorem with respect to the Gaussian Wiener measure, which is the law of the associated Gaussian process. In particular, it includes the…

Probability · Mathematics 2024-01-02 Qinpin Chen , Jian Sun , Bo Wu

It is well known that Brownian motion enjoys several distributional invariances such as the scaling property and the time reversal. In this paper, we prove another invariance of Brownian motion that is compatible with the time reversal. The…

Probability · Mathematics 2023-10-20 Yuu Hariya

We consider the limiting extremal process ${\mathcal X}$ of the particles of the binary branching Brownian motion. We show that after a shift by the logarithm of the derivative martingale $Z$, the rescaled "density" of particles, which are…

Probability · Mathematics 2021-11-03 Leonid Mytnik , Jean-Michel Roquejoffre , Lenya Ryzhik

In this paper, by using a Taylor development type formula, we show how it is possible to associate differential operators with stochastic differential equations driven by a fractional Brownian motion. As an application, we deduce that…

Probability · Mathematics 2007-05-23 Fabrice Baudoin , Laure Coutin

Fractional Brownian motions(fBMs) are not semimartingales so the classical theory of It\^o integral can't apply to fBMs. Wick integration as one of the applications of Malliavin calculus to stochastic analysis is a fine definition for fBMs.…

Probability · Mathematics 2025-04-01 Chunhao Cai , Cong Zhang
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