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Let $(W,H,\mu)$ be the classical Wiener space on $\R^d$. Assume that $X=(X_t(x))$ is a diffusion process satisfying the stochastic differential equation with diffusion and drift coefficients $\sigma: \R^n\to \R^n\otimes \R^d$, $b: \R^n\to…

Probability · Mathematics 2024-01-29 Ali Süleyman Üstünel

Score-based diffusion models have recently been extended to infinite-dimensional function spaces, with uses such as inverse problems arising from partial differential equations. In the Bayesian formulation of inverse problems, the aim is to…

Machine Learning · Computer Science 2026-05-12 Elizabeth L. Baker , Alexander Denker , Jes Frellsen

Starting from a sequence of independent Wright-Fisher diffusion processes on $[0,1]$, we construct a class of reversible infinite dimensional diffusion processes on $\DD_\infty:= \{{\bf x}\in [0,1]^\N: \sum_{i\ge 1} x_i=1\}$ with GEM…

Probability · Mathematics 2007-11-14 Shui Feng , Feng-Yu Wang

This is a study of a class of nonlocal nonlinear diffusion equations. We present a strong maximum principle for nonlocal time-dependent Dirichlet problems. Results are for bounded functions of space, rather than (semi)-continuous functions.…

Analysis of PDEs · Mathematics 2016-02-12 Ravi Shankar , Tucker Hartland

In this paper, we study Dirichlet problem for non-local operator on bounded domains in ${\mathbb R}^d$ $$ {\cal L}u = {\rm div}(A(x) \nabla (x)) + b(x) \cdot \nabla u(x) + \int_{{\mathbb R}^d} (u(y)-u(x) ) J(x, dy) , $$ where…

Probability · Mathematics 2025-01-14 Zhen-Qing Chen , Jun Peng

The Dirichlet form is a generalization of the Laplacian, heavily used in the study of many diffusion-like processes. In this paper we present a nonstandard representation theorem for the Dirichlet form, showing that the usual Dirichlet form…

Probability · Mathematics 2020-10-07 Robert M. Anderson , Haosui Duanmu , Aaron Smith

In this paper we carry out analysis and geometry for a class of infinite dimensional manifolds, namely, compound configuration spaces as a natural generalization of the work \cite{AKR97}. More precisely a differential geometry is…

Functional Analysis · Mathematics 2014-11-18 Yuri Kondratiev , Jose Luis Silva , Ludwig Streit

We introduce a framework for designing efficient diffusion models for $d$-dimensional symmetric-space Riemannian manifolds, including the torus, sphere, special orthogonal group and unitary group. Existing manifold diffusion models often…

Machine Learning · Computer Science 2025-05-29 Oren Mangoubi , Neil He , Nisheeth K. Vishnoi

We present a novel approach of discretizing variable coefficient diffusion operators in the context of meshfree generalized finite difference methods. Our ansatz uses properties of derived operators and combines the discrete Laplace…

Numerical Analysis · Mathematics 2024-06-21 Heinrich Kraus , Jörg Kuhnert , Pratik Suchde

Non-reversible lifts reduce the relaxation time of reversible diffusions at most by a square root. For reversible diffusions on domains in Euclidean space, or, more generally, on a Riemannian manifold with boundary, non-reversible lifts are…

Probability · Mathematics 2024-12-24 Andreas Eberle , Francis Lörler

Some preliminaries and basic facts regarding unbounded Wiener-Hopf operators (WH) are provided. WH with rational symbols are studied in detail showing that they are densely defined closed and have finite dimensional kernels and deficiency…

Functional Analysis · Mathematics 2021-05-18 Domenico P. L. Castrigiano

The asymptotic behaviour of empirical measures has plenty of studies. However, the research on conditional empirical measures is limited. Being the development of Wang \cite{eW1}, under the quadratic Wasserstein distance, we investigate the…

Probability · Mathematics 2022-04-29 Huaiqian Li , Bingyao Wu

Some little considerations concerning the application of the Theory of Dirichlet Forms to stocastic variational principle on riemannian manifolds are performed

Mathematical Physics · Physics 2007-05-23 Gavriel Segre

We recover the Riemannian gradient of a given function defined on interior points of a Riemannian submanifold in the Euclidean space based on a sample of function evaluations at points in the submanifold. This approach is based on the…

Machine Learning · Computer Science 2023-06-06 Alvaro Almeida Gomez , Antônio J. Silva Neto , Jorge P. Zubelli

We consider in this paper an area functional defined on submanifolds of fixed degree immersed into a graded manifold equipped with a Riemannian metric. Since the expression of this area depends on the degree, not all variations are…

Differential Geometry · Mathematics 2021-12-21 Giovanna Citti , Gianmarco Giovannardi , Manuel Ritoré

The problem of diffraction by a Dirichlet quarter-plane (a flat cone) in a 3D space is studied. The Wiener-Hopf equation for this case is derived and involves two unknown (spectral) functions depending on two complex variables. The aim of…

Analysis of PDEs · Mathematics 2021-02-09 R. C. Assier , A. V. Shanin

Stochastic processes are considered on free loop spaces, geometric loop and diffeomorphism groups of real and complex manifolds. They are used for investigations of Wiener differentiable quasi-invariant measures on such groups relative to…

Group Theory · Mathematics 2007-05-23 S. V. Ludkovsky

We start by revisiting the derivation of the variational formulae for the functional assigning to a bounded regular domain in a Riemannian manifold its first Dirichlet eigenvalue and extend it to (not necessarily bounded) domains in certain…

Differential Geometry · Mathematics 2024-10-11 Levi Lopes de Lima

In this note we define and study the stochastic process $X$ in link with a parabolic transmission operator $(A,D(A))$ in divergence form. The transmission operator involves a diffraction condition along a transmission boundary. To that aim…

Analysis of PDEs · Mathematics 2022-03-25 Pierre Etore , Miguel Martinez

The necessity of a Maximum Principle arises naturally when one is interested in the study of qualitative properties of solutions to partial differential equations. In general, to ensure the validity of these kind of principles one has to…

Analysis of PDEs · Mathematics 2023-10-04 Andrea Bisterzo