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Recently, a new approach in the fine analysis of stochastic processes sample paths has been developed to predict the evolution of the local regularity under (pseudo-)differential operators. In this paper, we study the sample paths of…

Probability · Mathematics 2013-08-29 Paul Balança , Erick Herbin

In the present paper, we study the chaotic representation property for certain families of square integrable martingales. For this purpose, we introduce the notion of compensated-covariation stability of such families. The chaotic…

Probability · Mathematics 2015-09-30 Paolo Di Tella , Hans-Jürgen Engelbert

We show that for a quantum $L^p$-martingale $(X(t))$, $p>2$, there exists a Doob-Meyer decomposition of the submartingale $(|X(t)|^2)$. A noncommutative counterpart of a classical process continuous with probability one is introduced, and a…

Operator Algebras · Mathematics 2007-05-23 Andrzej Luczak

The paper develops multiplicative compensation for complex-valued semimartingales and studies some of its consequences. It is shown that the stochastic exponential of any complex-valued semimartingale with independent increments becomes a…

Probability · Mathematics 2023-05-10 Aleš Černý , Johannes Ruf

We consider SDEs with (distributional) drift in negative Besov spaces and random initial condition and investigate them from two different viewpoints. In the first part we set up a martingale problem and show its well-posedness.We then…

Probability · Mathematics 2024-03-08 Elena Issoglio , Francesco Russo

In this paper we show the existence of a universal Skorohod measurable functional representation for a large class of semimartingale-driven stochastic differential equations. For this we prove that paths of the strong solutions of…

Probability · Mathematics 2025-03-26 Paweł Przybyłowicz , Verena Schwarz , Alexander Steinicke , Michaela Szölgyenyi

We consider a Poisson process $\eta$ on a measurable space $(\BY,\mathcal{Y})$ equipped with a partial ordering, assumed to be strict almost everwhwere with respect to the intensity measure $\lambda$ of $\eta$. We give a Clark-Ocone type…

Probability · Mathematics 2010-01-25 Guenter Last , Mathew D. Penrose

We prove that for every proper minor-closed class $M$ of matroids representable over a prime field, there exists a constant-competitive matroid secretary algorithm for the matroids in $M$. This result relies on the extremely powerful…

Combinatorics · Mathematics 2019-10-03 Tony Huynh , Peter Nelson

We are concerned with a stochastic mean curvature flow of graphs over a periodic domain of any space dimension. We establish existence of martingale solutions which are strong in the PDE sense and study their large-time behavior. Our…

Probability · Mathematics 2019-03-13 Nils Dabrock , Martina Hofmanová , Matthias Röger

The present paper is devoted to the second part of our project on asymmetric maximal inequalities, where we consider martingales in continuous time. Let $(\mathcal M,\tau)$ be a noncommutative probability space equipped with a continuous…

Probability · Mathematics 2016-11-07 Guixiang Hong , Marius Junge , Javier Parcet

In this work, we apply our newly proposed perturbative expansion technique to a quadratic growth FBSDE appearing in an incomplete market with stochastic volatility that is not perfectly hedgeable. By combining standard asymptotic expansion…

Computational Finance · Quantitative Finance 2012-09-07 Masaaki Fujii , Akihiko Takahashi

We present two examples of loss of the predictable representation property for semi-martingales by enlargement of the reference filtration. First of all we show that the predictable representation property for a square-integrable…

Probability · Mathematics 2016-01-12 Antonella Calzolari , Barbara Torti

We study the problem of existence and uniqueness of solutions of backward stochastic differential equations with two reflecting irregular barriers, $L^p$ data and generators satisfying weak integrability conditions. We deal with equations…

Probability · Mathematics 2016-11-04 Tomasz Klimsiak

In this paper, we study the non-asymptotic and asymptotic performances of the optimal robust policy and value function of robust Markov Decision Processes(MDPs), where the optimal robust policy and value function are solved only from a…

Machine Learning · Statistics 2022-08-16 Wenhao Yang , Liangyu Zhang , Zhihua Zhang

The random feature method (RFM) has demonstrated great potential in bridging traditional numerical methods and machine learning techniques for solving partial differential equations (PDEs). It retains the advantages of mesh-free approaches…

Numerical Analysis · Mathematics 2025-05-02 Mikhail Kuvakin , Zijian Mei , Jingrun Chen

We establish weak well-posedness for critical symmetric stable driven SDEs in R d with additive noise Z, d $\ge$ 1. Namely, we study the case where the stable index of the driving process Z is $\alpha$ = 1 which exactly corresponds to the…

Probability · Mathematics 2020-01-14 Paul-Eric Chaudru de Raynal , Stephane Menozzi , Enrico Priola

We prove the existence of weak solutions for distribution-dependent stochastic Volterra equations under linear growth and continuity conditions on the coefficients and mild regularity assumptions on the kernels, including singular kernels.…

Probability · Mathematics 2026-04-28 Martin Bergerhausen , David J. Prömel

Markovian growth-fragmentation processes introduced by Bertoin extend the pure fragmentation model by allowing the fragments to grow larger or smaller between dislocation events. What becomes of the known asymptotic behaviors of…

Probability · Mathematics 2019-12-11 Benjamin Dadoun

As is known, a process of form $\int_0^t\eta_sd\langle B\rangle_s-\int_0^t2G(\eta_s)ds$, $\eta\in M^1_G(0,T)$, is a non-increasing $G$-martingale. In this paper, we shall show that a non-increasing $G$-martingale could not be form of…

Probability · Mathematics 2016-07-05 Yongsheng Song

The Schr\"odinger Bridge (SB) problem has become a fundamental tool in computational optimal transport and generative modeling. To address this problem, ideal methods such as Iterative Proportional Fitting and Iterative Markovian Fitting…

Machine Learning · Statistics 2025-10-27 Marta Gentiloni Silveri , Giovanni Conforti , Alain Durmus