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Wetterich's equation and corresponding flows of effective average actions are used frequently in theoretical physics to study the properties of quantum field theories. Under appropriate conditions, Wetterich's equation also holds for Radon…

Functional Analysis · Mathematics 2025-12-09 Jobst Ziebell

In this work, a generalised version of the central limit theorem is proposed for nonlinear functionals of the empirical measure of i.i.d. random variables, provided that the functional satisfies some regularity assumptions for the…

Probability · Mathematics 2021-12-07 Benjamin Jourdain , Alvin Tse

In this paper, we study the stochastic Hamiltonian flow in Wasserstein manifold, the probability density space equipped with $L^2$-Wasserstein metric tensor, via the Wong--Zakai approximation. We begin our investigation by showing that the…

Probability · Mathematics 2021-12-01 Jianbo Cui , Shu Liu , Haomin Zhou

A principled method to obtain approximate solutions of general constrained integer optimization problems is introduced. The approach is based on the calculation of a mean field probability distribution for the decision variables which is…

Optimization and Control · Mathematics 2013-05-08 Arturo Berrones , Jonás Velasco , Juan Banda

An integer-valued moving average (INMA) model for count random fields is proposed and investigated. Closed-form expressions are derived for both its marginal distribution and spatial dependence structure, for arbitrary model order and also…

Statistics Theory · Mathematics 2026-05-25 Angelika Silbernagel , Christian H. Weiß

Conditional Kendall's tau is a measure of dependence between two random variables, conditionally on some covariates. We assume a regression-type relationship between conditional Kendall's tau and some covariates, in a parametric setting…

Statistics Theory · Mathematics 2018-11-21 Alexis Derumigny , Jean-David Fermanian

In this paper we study the structure of square integrable functionals measurable with respect to coalescing stochastic flows. The case of $L^2$ space generated by the process $\eta(\cdot)=w(\min(\tau,\cdot)),$ where $w$ is a Brownian motion…

Probability · Mathematics 2013-10-24 Andrey A. Dorogovtsev , Georgii V. Riabov

Finite mixture models are an important tool in the statistical analysis of data, for example in data clustering. The optimal parameters of a mixture model are usually computed by maximizing the log-likelihood functional via the…

Machine Learning · Statistics 2020-11-30 Laura Aquilanti , Simone Cacace , Fabio Camilli , Raul De Maio

We prove quantitative estimates for flows of vector fields subject to anisotropic regularity conditions: some derivatives of some components are (singular integrals of) measures, while the remaining derivatives are (singular integrals of)…

Analysis of PDEs · Mathematics 2014-12-09 Anna Bohun , Francois Bouchut , Gianluca Crippa

The stochastic vacuum model description of a heavy meson is discussed in the context of a gauge invariant approach where Wilson loop expectation values appear naturally in the O($v^2$) spin-orbit Hamiltonian. These expectation values have…

High Energy Physics - Phenomenology · Physics 2007-05-23 K. Williams

In this paper we extend the DiPerna-Lions theory on ODEs with Sobolev vector fields to the setting of abstract Wiener spaces.

Analysis of PDEs · Mathematics 2008-03-11 Luigi Ambrosio , Alessio Figalli

In this paper we introduce a new measure of conditional dependence between two random vectors ${\boldsymbol X}$ and ${\boldsymbol Y}$ given another random vector $\boldsymbol Z$ using the ball divergence. Our measure characterizes…

Statistics Theory · Mathematics 2024-08-01 Bilol Banerjee , Bhaswar B. Bhattacharya , Anil K. Ghosh

We provide necessary and sufficient conditions for stochastic invariance of finite dimensional submanifolds with boundary in Hilbert spaces for stochastic partial differential equations driven by Wiener processes and Poisson random…

Probability · Mathematics 2014-06-23 Damir Filipovic , Stefan Tappe , Josef Teichmann

We observe stationary random tessellations $X=\{\Xi_n\}_{n\ge1}$ in $\mathbb{R}^d$ through a convex sampling window $W$ that expands unboundedly and we determine the total $(k-1)$-volume of those $(k-1)$-dimensional manifold processes which…

Probability · Mathematics 2007-09-14 Lothar Heinrich , Hendrik Schmidt , Volker Schmidt

Conditional Monte Carlo refers to sampling from the conditional distribution of a random vector X given the value T(X) = t for a function T(X). Classical conditional Monte Carlo methods were designed for estimating conditional expectations…

Methodology · Statistics 2020-10-15 Bo Henry Lindqvist , Rasmus Erlemann , Gunnar Taraldsen

Based on the concept of manifold valued generalized functions we initiate a study of nonlinear ordinary differential equations with singular (in particular: distributional) right hand sides in a global setting. After establishing several…

Functional Analysis · Mathematics 2007-05-23 Michael Kunzinger , Michael Oberguggenberger , Roland Steinbauer , James A. Vickers

We construct a pathwise calculus for functionals of integer-valued measures and use it to derive an martingale representation formula with respect to a large class of integer-valued random measures. Using these results, we extend the…

Probability · Mathematics 2020-02-28 Pierre M. Blacque-Florentin , Rama Cont

This paper proposes a new mathematical formulation for flow measurement based on the inverse source problem for wave equations with partial boundary measurement. Inspired by the design of acoustic Doppler current profilers (ADCPs), we…

Optimization and Control · Mathematics 2025-03-19 Jiwei Li , Lingyun Qiu , Zhongjing Wang , Hui Yu

We study the Neumann and Dirichlet problems for the total variation flow in metric measure spaces. We prove existence and uniqueness of weak solutions and study their asymptotic behaviour. Furthermore, in the Neumann problem we provide a…

Analysis of PDEs · Mathematics 2021-05-25 Wojciech Górny , José M. Mazón

By using Malliavin calculus, Bismut type formulas are established for the Lions derivative of $P_tf(\mu):=\mathbb E f(X_t^\mu)$, where $t>0,$ $ f $ is a bounded measurable function, and $X_t^\mu$ solves a distribution dependent SDE with…

Probability · Mathematics 2021-03-12 Panpan Ren , Feng-Yu Wang