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We develop a new method to estimate the area, and more generally the intrinsic volumes, of a compact subset $X$ of $\mathbb{R}^d$ from a set $Y$ that is close in the Hausdorff distance. This estimator enjoys a linear rate of convergence as…

Metric Geometry · Mathematics 2024-07-22 David Cohen-Steiner , Antoine Commaret

In recent years, manifold methods have moved into focus as tools for dimension reduction. Assuming that the high-dimensional data actually lie on or close to a low-dimensional nonlinear manifold, these methods have shown convincing results…

Machine Learning · Statistics 2020-12-23 Moritz Herrmann , Fabian Scheipl

For functional data lying on an unknown nonlinear low-dimensional space, we study manifold learning and introduce the notions of manifold mean, manifold modes of functional variation and of functional manifold components. These constitute…

Statistics Theory · Mathematics 2012-05-29 Dong Chen , Hans-Georg Müller

The interaction between discrete and continuous mathematics lies at the heart of many fundamental problems in applied mathematics and computational sciences. In this paper we discuss the problem of discretizing vector-valued functions…

Numerical Analysis · Mathematics 2020-05-29 Paweł Dłotko , Thomas Wanner

In a setting, where only exit measures are given, as they are associated with a right continuous strong Markov process on a separable metric space, we provide simple criteria for scaling invariant H\"older continuity of bounded harmonic…

Analysis of PDEs · Mathematics 2016-11-10 Wolfhard Hansen

A new version of the Hadwiger theorem on convex functions is established and an explicit representation of functional intrinsic volumes is found using new functional Cauchy-Kubota formulas. In addition, connections between functional…

Functional Analysis · Mathematics 2025-07-28 Andrea Colesanti , Monika Ludwig , Fabian Mussnig

We study the most elementary aspects of harmonic analysis on a homogeneous space of a deformation of the two-dimensional Euclidean group, admitting generalizations to dimensions three and four, whose quantum parameter has the physical…

q-alg · Mathematics 2008-02-03 F. Bonechi , R. Giachetti , M. A. del Olmo , E. Sorace , M. Tarlini

We propose a generalization of two classes of Lie-Hamilton systems on the Euclidean plane to two-dimensional curved spaces, leading to novel Lie-Hamilton systems on Riemannian spaces (flat $2$-torus, product of hyperbolic lines, sphere and…

Mathematical Physics · Physics 2024-11-26 Rutwig Campoamor-Stursberg , Oscar Carballal , Francisco J. Herranz

A Hamiltonian with two degrees of freedom is said to be superintegrable if it admits three functionally independent integrals of the motion. This property has been extensively studied in the case of two-dimensional spaces of constant…

Mathematical Physics · Physics 2007-05-23 E. G. Kalnins , J. M. Kress , P. Winternitz

Hypersurfaces embedded in conformal manifolds appear frequently as boundary data in boundary-value problems in cosmology and string theory. Viewed as the non-null conformal infinity of a spacetime, we consider hypersurfaces embedded in a…

Differential Geometry · Mathematics 2023-02-06 Samuel Blitz

We discuss hypersurface motions in Riemannian manifolds whose normal velocity is a function of the induced hypersurface volume element and derive a second order partial differential equation for the corresponding time function $\tau(x)$ at…

High Energy Physics - Theory · Physics 2009-10-28 Martin Bordemann , Jens Hoppe

Consider an ergodic stationary random field $A$ on the ambient space $\mathbb R^d$. In order to establish concentration properties for nonlinear functions $Z(A)$, it is standard to appeal to functional inequalities like Poincar\'e or…

Probability · Mathematics 2019-10-11 Mitia Duerinckx , Antoine Gloria

Nondegenerate covariance, correlation and spectral density matrices are necessarily symmetric or Hermitian and positive definite. The main contribution of this paper is the development of statistical data depths for collections of Hermitian…

Methodology · Statistics 2019-11-12 Joris Chau , Hernando Ombao , Rainer von Sachs

Manifold reconstruction has been extensively studied for the last decade or so, especially in two and three dimensions. Recently, significant improvements were made in higher dimensions, leading to new methods to reconstruct large classes…

Computational Geometry · Computer Science 2007-12-18 Frédéric Chazal , Steve Oudot

We introduce a framework for uncertainty estimation that both describes and extends many existing methods. We consider typical hyperparameters involved in classical training as random variables and marginalise them out to capture various…

Machine Learning · Computer Science 2021-07-07 Francesco Farina , Lawrence Phillips , Nicola J Richmond

[1] investigates advanced connotations of Hardy and Rellich-type inequalities on complete noncompact Riemannian manifolds, delving on deriving inequalities that incorporate poignant weight functions. These inequalities prolongate classical…

Differential Geometry · Mathematics 2024-11-13 Shouvik Datta Choudhury

We study the continuous solutions of several classical functional equations by using the properties of the spaces of continuous functions which are invariant under some elementary linear trans-formations. Concretely, we use that the sets of…

Classical Analysis and ODEs · Mathematics 2013-10-30 J. M. Almira , Kh. F. Abu-Helaiel

Associated to any finite metric space are a large number of objects and quantities which provide some degree of structural or geometric information about the space. In this paper we show that in the setting of subsets of weighted Hamming…

Functional Analysis · Mathematics 2024-09-19 Ian Doust , Anthony Weston

In this short note, we hope to give a rapid induction for non-experts into the world of Differential Harnack inequalities, which have been so influential in geometric analysis and probability theory over the past few decades. At the…

Differential Geometry · Mathematics 2013-01-09 Sebastian Helmensdorfer , Peter Topping

In this paper, we present a method of embedding physics data manifolds with metric structure into lower dimensional spaces with simpler metrics, such as Euclidean and Hyperbolic spaces. We then demonstrate that it can be a powerful step in…

High Energy Physics - Phenomenology · Physics 2023-08-02 Sang Eon Park , Philip Harris , Bryan Ostdiek