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We give an abridged account of a continued string of studies in condensed matter physics and in complex systems that span five decades. We provide links to access abstracts and full texts of a selected list of publications. The studies were…

Statistical Mechanics · Physics 2024-01-15 Alberto Robledo , Carlos Velarde

Functional determinants for the scalar Laplacian on spherical caps and slices, flat balls, shells and generalised cylinders are evaluated in two, three and four dimensions using conformal techniques. Both Dirichlet and Robin boundary…

High Energy Physics - Theory · Physics 2010-04-06 J. S. Dowker , J. S. Apps

We introduce a family of local inhomogeneous mark-weighted summary statistics, of order two and higher, for general marked point processes. Depending on how the involved weight function is specified, these summary statistics capture…

Methodology · Statistics 2024-03-13 Nicoletta D'Angelo , Giada Adelfio , Jorge Mateu , Ottmar Cronie

We present a determinantal point process (DPP) inspired alternative to non-maximum suppression (NMS) which has become an integral step in all state-of-the-art object detection frameworks. DPPs have been shown to encourage diversity in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Samik Some , Mithun Das Gupta , Vinay P. Namboodiri

This paper is part of a program to understand the parameter spaces of dynamical systems generated by meromorphic functions with finitely many singular values. We give a full description of the parameter space for a specific family based on…

Complex Variables · Mathematics 2022-01-24 Tao Chen , Yunping Jiang , Linda Keen

We propose new summary statistics for intensity-reweighted moment stationary point processes that generalise the well known J-, empty space, and nearest-neighbour distance distribution functions, represent them in terms of generating…

Methodology · Statistics 2010-08-27 M. N. M. van Lieshout

The aim of this paper is to define a nonlinear least squares estimator for the spectral parameters of a spherical autoregressive process of order 1 in a parametric setting. Furthermore, we investigate on its asymptotic properties, such as…

Statistics Theory · Mathematics 2021-07-20 Alessia Caponera , Claudio Durastanti

In this article, recent results about point processes are used in sampling theory. Precisely, we define and study a new class of sampling designs: determinantal sampling designs. The law of such designs is known, and there exists a simple…

Methodology · Statistics 2025-08-27 Vincent Loonis , Xavier Mary

We discuss the practice of directly or indirectly assuming a model for the number of points when modelling spatial point patterns even though it is rarely possible to validate such a model in practice since most point pattern data consist…

Methodology · Statistics 2022-02-10 Jesper Møller , Ninna Vihrs

We provide new limit theory for functionals of a general class of processes lying at the boundary between stationarity and nonstationarity -- what we term weakly nonstationary processes (WNPs). This includes, as leading examples, fractional…

Statistics Theory · Mathematics 2020-08-17 James A. Duffy , Ioannis Kasparis

We study a nonlinear semigroup associated to a nonexpansive mapping on a Hadamard space and establish its weak convergence to a fixed point. A discrete-time counterpart of such a semigroup, the proximal point algorithm, turns out to have…

Functional Analysis · Mathematics 2014-07-25 Miroslav Bacak , Simeon Reich

We propose an alternative to $k$-nearest neighbors for functional data whereby the approximating neighboring curves are piecewise functions built from a functional sample. Using a locally defined distance function that satisfies…

Methodology · Statistics 2021-06-02 Antonio Elías , Raúl Jiménez , Joe Yukich

In this paper we develop statistical inference tools for high dimensional functional time series. We introduce a new concept of physical dependent processes in the space of square integrable functions, which adopts the idea of basis…

Statistics Theory · Mathematics 2020-03-16 Zhou Zhou , Holger Dette

Density-potential functional theory (DPFT) is an alternative formulation of orbital-free density functional theory that may be suitable for modeling the electronic structure of large systems. To date, DPFT has been applied mainly to quantum…

Materials Science · Physics 2023-04-21 Martin-Isbjörn Trappe , William C. Witt , Sergei Manzhos

This paper investigates the information geometrical structure of a determinantal point process (DPP). It demonstrates that a DPP is embedded in the exponential family of log-linear models. The extent of deviation from an exponential family…

Statistics Theory · Mathematics 2024-04-18 Hideitsu Hino , Keisuke Yano

In the literature on spatial point processes, there is an emerging challenge in studying marked point processes with points being labelled by functions. In this paper, we focus on point processes living on linear networks and, from distinct…

Methodology · Statistics 2024-07-11 Matthias Eckardt , Jorge Mateu , Mehdi Moradi

In the context of functional data analysis, probability density functions as non-negative functions are characterized by specific properties of scale invariance and relative scale which enable to represent them with the unit integral…

Numerical Analysis · Mathematics 2019-12-19 Jitka Machalova , Renata Talska , Karel Hron , Ales Gaba

A geometry-based density functional theory is presented for mixtures of hard spheres, hard needles and hard platelets; both the needles and the platelets are taken to be of vanishing thickness. Geometrical weight functions that are…

Soft Condensed Matter · Physics 2009-11-11 Ansgar Esztermann , Hendrik Reich , Matthias Schmidt

To analyse interaction in marked spatio-temporal point processes (MSTPPs), we introduce marked (cross) second-order reduced moment measures and K-functions for general inhomogeneous second-order intensity reweighted stationary MSTPPs. These…

Methodology · Statistics 2016-11-16 Adina Iftimi , Ottmar Cronie , Francisco Montes

We establish sensitivity analysis on the sphere. We present formulas that allow us to decompose a function $f\colon \mathbb S^d\rightarrow \mathbb R$ into a sum of terms $f_{\boldsymbol u,\boldsymbol \xi}$. The index $\boldsymbol u$ is a…

Numerical Analysis · Mathematics 2026-05-15 Laura Weidensager
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