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A new weighted Hardy-type inequality for functions from the Sobolev space $W_{p}^{1}$ is proved. It is assumed that functions vanish on small alternating pieces of the boundary. The proved inequality generalizes the classical known weighted…

Classical Analysis and ODEs · Mathematics 2026-04-17 Yu. O. Koroleva

We obtain the local well-posedness of a moving boundary problem that describes the swelling of a pocket of water within an infinitely thin elongated pore. Our result involves fine a priori estimates of the moving boundary evolution, Banach…

Analysis of PDEs · Mathematics 2018-05-01 Kota Kumazaki , Adrian Muntean

We develop efficient and high-order accurate finite difference methods for elliptic partial differential equations in complex geometry in the Difference Potentials framework. The main novelty of the developed schemes is the use of local…

Numerical Analysis · Mathematics 2023-06-28 Qing Xia

Shape estimation and object reconstruction are common problems in image analysis. Mathematically, viewing objects in the image plane as random sets reduces the problem of shape estimation to inference about sets. Currently existing…

Methodology · Statistics 2009-03-12 Larissa I. Stanberry , Hanna K. Jankowski

Substatic Riemannian manifolds with minimal boundary arise naturally in General Relativity as spatial slices of static spacetimes satisfying the Null Energy Condition. Moreover, they constitute a vast generalization of nonnegative Ricci…

Differential Geometry · Mathematics 2023-07-28 Stefano Borghini , Mattia Fogagnolo

This work establishes computable bounds between f-divergences for probability measures within a generalized quasi-$\varepsilon_{(M,m)}$-neighborhood framework. We make the following key contributions. (1) a unified characterization of local…

Information Theory · Computer Science 2025-08-12 Xinchun Yu , Shuangqing Wei , Xiao-Ping Zhang

The notion of pointwise differentials for distributions is a way to extract local information of distributions by rescaling the distribution at a point. In this paper, we study the pointwise differentials for distributions corresponding to…

Classical Analysis and ODEs · Mathematics 2025-03-06 Yu-Tong Liu

A functorial semi-norm on singular homology is a collection of semi-norms on the singular homology groups of spaces such that continuous maps between spaces induce norm-decreasing maps in homology. Functorial semi-norms can be used to give…

Geometric Topology · Mathematics 2015-03-11 Diarmuid Crowley , Clara Loeh

We investigate linear parabolic equations in divergence form with singular coefficients and non-smooth boundary data. When the diffusion, drift, or potential terms, as well as the initial or boundary conditions, are distributions rather…

Analysis of PDEs · Mathematics 2026-02-10 Arshyn Altybay , Alibek Yeskermessuly

A novel algorithm is proposed for quantitative comparisons between compact surfaces embedded in the three-dimensional Euclidian space. The key idea is to identify those objects with the associated surface measures and compute a weak…

Numerical Analysis · Mathematics 2024-01-17 Kazuki Koga

A basilar property and a useful tool in the theory of Sobolev spaces is the density of smooth compactly supported functions in the space $W^{k,p}(\R^n)$ (i.e. the functions with weak derivatives of orders $0$ to $k$ in $L^p$). On Riemannian…

Analysis of PDEs · Mathematics 2023-02-15 Giona Veronelli

We consider the Steklov problem on differential $p$-forms defined by M. Karpukhin and present geometric eigenvalue bounds in the setting of warped product manifolds in various scenarios. In particular, we obtain Escobar type lower bounds…

Differential Geometry · Mathematics 2025-03-05 Tirumala Chakradhar

We consider minimization of functions that are compositions of convex or prox-regular functions (possibly extended-valued) with smooth vector functions. A wide variety of important optimization problems fall into this framework. We describe…

Optimization and Control · Mathematics 2015-04-24 A. S. Lewis , S. J. Wright

Supervised manifold learning methods learn data representations by preserving the geometric structure of data while enhancing the separation between data samples from different classes. In this work, we propose a theoretical study of…

Machine Learning · Computer Science 2018-01-08 Elif Vural , Christine Guillemot

In metric measure spaces, we study boundary traces of BV functions in domains equipped with a doubling measure and supporting a Poincar\'e inequality, but possibly having a very large and irregular boundary. We show that the trace exists in…

Functional Analysis · Mathematics 2021-07-15 Panu Lahti

We consider the regression problem of estimating functions on $\mathbb{R}^D$ but supported on a $d$-dimensional manifold $ \mathcal{M} \subset \mathbb{R}^D $ with $ d \ll D $. Drawing ideas from multi-resolution analysis and nonlinear…

Machine Learning · Statistics 2021-01-14 Wenjing Liao , Mauro Maggioni , Stefano Vigogna

A key issue in dimension reduction of dissipative dynamical systems with spectral gaps is the identification of slow invariant manifolds. We present theoretical and numerical results for a variational approach to the problem of computing…

Dynamical Systems · Mathematics 2012-11-30 Dirk Lebiedz , Jochen Siehr , Jonas Unger

Given a unital algebra $\mathscr A$ of locally Lipschitz functions defined over a metric measure space $({\mathrm X},{\mathsf d},\mathfrak m)$, we study two associated notions of function of bounded variation and their relations: the space…

Functional Analysis · Mathematics 2026-04-08 Enrico Pasqualetto , Giacomo Enrico Sodini

In this paper, we consider the infinite-dimensional integration problem on weighted reproducing kernel Hilbert spaces with norms induced by an underlying function space decomposition of ANOVA-type. The weights model the relative importance…

Numerical Analysis · Mathematics 2021-09-21 Jan Baldeaux , Michael Gnewuch

Multivariate functions encountered in high-dimensional uncertainty quantification problems often vary most strongly along a few dominant directions in the input parameter space. We propose a gradient-based method for detecting these…

Analysis of PDEs · Mathematics 2019-11-11 Olivier Zahm , Paul Constantine , Clémentine Prieur , Youssef Marzouk