English
Related papers

Related papers: Nonlocal Bounded Variations with Applications

200 papers

In this work we study qualitative properties of real analytic bounded maps. The main tool is approximation of real valued functions analytic in rectangular domains of the complex plane by continued g-fractions of Wall. As an application,…

Dynamical Systems · Mathematics 2018-08-21 Alexei Tsygvintsev

Optimal embeddings for fractional Orlicz-Sobolev spaces into (generalized) Campanato spaces on the Euclidean space are exhibited. Embeddings into vanishing Campanato spaces are also characterized. Sharp embeddings into…

Functional Analysis · Mathematics 2025-06-17 Angela Alberico , Andrea Cianchi , Luboš Pick , Lenka Slavíková

We study the predual of the space of functions of bounded variation defined over a metric measure space $({\rm X},{\sf d},\mathfrak m)$ with $\mathfrak m$ finite. More specifically, for any exponent $p\in(1,\infty)$ we construct an…

Functional Analysis · Mathematics 2025-11-21 Enrico Pasqualetto

In a previous paper the boundedness properties of Riesz Potentials, Bessel potentials and Fractional Derivatives were studied in detail on Gaussian Besov-Lipschitz spaces $B_{p,q}^{\alpha}(\gamma_d)$. In this paper we will continue our…

Classical Analysis and ODEs · Mathematics 2012-09-28 A. Eduardo Gatto , Ebner Pineda , Wilfredo Urbina

We introduce fractional flat space, described by a continuous geometry with constant non-integer Hausdorff and spectral dimensions. This is the analogue of Euclidean space, but with anomalous scaling and diffusion properties. The basic tool…

High Energy Physics - Theory · Physics 2013-01-22 Gianluca Calcagni

The paper concerns the investigation of nonconvex and nondifferentiable integral functionals on general Banach spaces, which may not be reflexive and/or separable. Considering two major subdifferentials of variational analysis, we derive…

Optimization and Control · Mathematics 2016-03-28 Boris S. Mordukhovich , Nobusumi Sagara

A study on the notion of covariant derivatives in flat and curved space-time via It\^o-Wiener processes, when subjected to stochastic processes, is presented. Going into details, there is an analysis of the following topics: (i) Besov…

Probability · Mathematics 2023-04-26 Edoardo Niccolai

We develop the theory of tamed spaces which are Dirichlet spaces with distribution-valued lower bounds on the Ricci curvature and investigate these from an Eulerian point of view. To this end we analyze in detail singular perturbations of…

Functional Analysis · Mathematics 2020-09-08 Matthias Erbar , Chiara Rigoni , Karl-Theodor Sturm , Luca Tamanini

We study the equation of one-dimensional quasistatic nonlinear viscoelasticity with Dirichlet boundary conditions, in the particular case that the underlying dissipation geometry (provided by the viscosity) is comparable to the Bhattacharya…

Analysis of PDEs · Mathematics 2026-05-12 Alexander Mielke , Billy Sumners

Let $(\mathcal{M},g_0)$ be a compact Riemannian manifold-with-boundary. We present a new proof of the classical Gaffney's inequality for differential forms in boundary value spaces over $\mathcal{M}$, via the variational approach \`{a} la…

Analysis of PDEs · Mathematics 2026-01-30 Siran Li

Scalar-on-image regression aims to investigate changes in a scalar response of interest based on high-dimensional imaging data. We propose a novel Bayesian nonparametric scalar-on-image regression model that utilises the spatial coordinates…

Methodology · Statistics 2022-06-23 Mica Teo Shu Xian , Sara Wade

Sticky diffusion processes on bounded domains spend finite time (and finite mean time) on the lower-dimensional space given by the boundary. Once the process hits the boundary, then it starts again after a random amount of time. While on…

Probability · Mathematics 2026-05-19 Mirko D'Ovidio

We describe a procedure to introduce Sobolev spaces and the semigroup generated by the fractional Dirichlet Laplacian on an arbitrary domain of $\R^d$. In particular, the well-definedness of the spaces of both non-homogeneous and…

Functional Analysis · Mathematics 2022-03-30 Reinhard Farwig , Tsukasa Iwabuchi

We study properties of the classical fractional Sobolev spaces (or Bessel potential spaces) on non-Lipschitz subsets of $\mathbb{R}^n$. We investigate the extent to which the properties of these spaces, and the relations between them, that…

Functional Analysis · Mathematics 2022-08-29 Simon N. Chandler-Wilde , David P. Hewett , Andrea Moiola

Variational inference (VI) is a popular method for approximating intractable posterior distributions in Bayesian inference and probabilistic machine learning. In this paper, we introduce a general framework for quantifying the statistical…

Statistics Theory · Mathematics 2025-07-18 Chenyang Zhong , Sumit Mukherjee , Bodhisattva Sen

As a generalization of the Fourier transform, the fractional Fourier transform was introduced and has been further investigated both in theory and in applications of signal processing. We obtain a sampling theorem on shift-invariant spaces…

Functional Analysis · Mathematics 2013-02-12 Sinuk Kang

In this article we investigate mathematically the variant of post-Newtonian mechanics using generalized fractional derivatives. The relativistic-covariant generalization of the classical equations for gravitational field is studied. The…

General Relativity and Quantum Cosmology · Physics 2011-01-21 V. Kobelev

This paper studies topological duals of Banach function spaces (BFS). We assume a finite measure but our arguments extend to general locally convex function spaces whose topology is generated by seminorms that satisfy the usual BFS axioms.…

Probability · Mathematics 2020-12-11 Teemu Pennanen , Ari-Pekka Perkkiö

We study the boundary behaviour of a variant of the Fridman's invariant function (defined in terms of the Bergman metric) on Levi corank one domains, strongly pseudoconvex domains, smoothly bounded convex domains in $ \mathbb{C}^n $ and…

Complex Variables · Mathematics 2024-01-09 Rahul Kumar , Prachi Mahajan

Sampling a target probability distribution with an unknown normalization constant is a fundamental challenge in computational science and engineering. Recent work shows that algorithms derived by considering gradient flows in the space of…

Machine Learning · Statistics 2024-03-12 Yifan Chen , Daniel Zhengyu Huang , Jiaoyang Huang , Sebastian Reich , Andrew M Stuart