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Related papers: Analysis on Wiener Space and Applications

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These notes represent a much expanded and updated version of the \textquotedblleft mini course\textquotedblright that the author gave at the ETH (Z\"{u}rich) and the University of Z\"{u}rich in February of 1995. The purpose of these notes…

Probability · Mathematics 2007-05-23 Bruce K. Driver

This paper deals with the study of the Malliavin calculus of Euclidean motions on Wiener space, (i.e. transformations induced by general measure preserving transformations, called `rotations', and H-valued shifts) and the associated flows…

Probability · Mathematics 2007-05-23 Y. Hu , A. S. Ustunel , M. Zakai

We use Malliavin operators in order to prove quantitative stable limit theorems on the Wiener space, where the target distribution is given by a possibly multidimensional mixture of Gaussian distributions. Our findings refine and generalize…

Probability · Mathematics 2016-02-16 Ivan Nourdin , David Nualart , Giovanni Peccati

The aim of this study is to clarify the consequences of recent theoretical results for the numerical computation of expectation by the shift method, and in particular to yield sufficient criteria for the existence of speed of convergence of…

Probability · Mathematics 2007-05-23 Nicolas Bouleau

This book is an introduction to the nascent field of Fourier analysis on polytopes, and cones. There is a rapidly growing number of applications of these methods, so it is appropriate to invite students, as well as professionals, to the…

Combinatorics · Mathematics 2023-02-21 Sinai Robins

Malliavin Calculus can be seen as a differential calculus on Wiener spaces. We present the notion of stochastic manifold for which the Malliavin Calculus plays the same role as the classical differential calculus for the differential…

Probability · Mathematics 2014-06-05 Anatole Khelif , Alain Tarica

We introduce the concept of functions of locally bounded variation on abstract Wiener spaces and study their properties. Some nontrivial examples and applications to stochastic analysis are also discussed.

Probability · Mathematics 2019-09-16 Masanori Hino

Wiener spaces are in many ways the decisive setting for fundamental results on Gaussian measures: large deviations (Schilder), quasi-invariance (Cameron--Martin), differential calculus (Malliavin), support description (Stroock--Varadhan),…

Probability · Mathematics 2025-10-03 Gideon Chiusole , Peter K. Friz

The present report, has been inspired by the need of the author and its colleagues to understand the underlying theory of Wirtinger's Calculus and to further extend it to include the kernel case. The aim of the present manuscript is…

Machine Learning · Computer Science 2010-06-02 P. Bouboulis

We introduce the notion of {\em covariance measure structure} for square integrable stochastic processes. We define Wiener integral, we develop a suitable formalism for stochastic calculus of variations and we make Gaussian assumptions only…

Probability · Mathematics 2007-05-23 Ida Kruk , Francesco Russo , Ciprian Tudor

The aim of this text is to provide a linguistically accessible, but comprehensive introduction into a variety of topics in dynamical systems and its applications. Whilst preliminary knowledge of dynamical systems is useful, it is not…

Dynamical Systems · Mathematics 2026-01-09 Eugene Tan , David Walker , Michael Small , Braden Thorne

Some parts of stochastic analysis on curved spaces are revisted. A concise proof of the quasi-invariance of the Wiener measure on the path spaces over a Riemannian manifold is presented. The shifts are allowed to be in the Cameron-Martin…

Probability · Mathematics 2013-11-19 Adnan Aboulalaa

These Lecture Notes are a brief introduction to the Malliavin calculus. In particular, different notions of Malliavin derivative found in the literature are considered and compared.

Probability · Mathematics 2025-02-13 Luciano Tubaro , Margherita Zanella

We study optimization problems whereby the optimization variable is a probability measure. Since the probability space is not a vector space, many classical and powerful methods for optimization (e.g., gradients) are of little help. Thus,…

Optimization and Control · Mathematics 2024-06-18 Nicolas Lanzetti , Antonio Terpin , Florian Dörfler

This book contains a large number of exercises related to different stochastic disciplines. Difficulty of the problems varies from the basic level in the first chapter up to the analysis of articles in Probability, Statistics and Computer…

The goal of this thesis is twofold; introduce the fundamentals of Bayesian inference and computation focusing on astronomical and cosmological applications, and present recent advances in probabilistic computational methods developed by the…

Instrumentation and Methods for Astrophysics · Physics 2023-03-31 Minas Karamanis

We characterise modulation spaces by suitable Wiener estimates on the short-time Fourier transforms of the involved functions and distributions. We use the results to refine some formulae on periodic distributions with Lebesgue estimates on…

Functional Analysis · Mathematics 2019-03-20 Joachim Toft

Quadratic Wiener functionals are investigated systematically through transformations of order one on the Wiener space with the help of Malliavin calculus. The bi-directional relationship between quadratic Wiener functionals and…

Probability · Mathematics 2026-03-03 Setsuo Taniguchi

This text is a support for different courses of the master of Mechanics of the University Paris-Saclay. The content of this text is an introduction, for graduate students, to tensor algebra and analysis. Far from being exhaustive, the text…

History and Overview · Mathematics 2025-01-13 Paolo Vannucci

The Wiener Sausage, the volume traced out by a sphere attached to a Brownian particle, is a classical problem in statistics and mathematical physics. Initially motivated by a range of field-theoretic, technical questions, we present a…

Statistical Mechanics · Physics 2017-09-01 Stefan Nekovar , Gunnar Pruessner
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