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Voronoi intensity estimators, which are non-parametric estimators for intensity functions of point processes, are both parameter-free and adaptive; the intensity estimate at a given location is given by the reciprocal size of the…

A new and rather broad class of stationary (i.e. stochastically translation invariant) random tessellations of the $d$-dimensional Euclidean space is introduced, which are called shape-driven nested Markov tessellations. Locally, these…

Probability · Mathematics 2013-09-16 Tomasz Schreiber , Christoph Thaele

Probabilistic circuits (PCs) enable exact and tractable inference but employ data independent mixture weights that limit their ability to capture local geometry of the data manifold. We propose Voronoi tessellations (VT) as a natural way to…

Machine Learning · Computer Science 2026-03-13 Sahil Sidheekh , Sriraam Natarajan

In modern telecommunications, spatial burstiness of data traffic poses challenges to traditional Poisson-based models. This paper describes application of thinning-stable point processes, which provide a more appropriate framework for…

Applications · Statistics 2025-05-12 Sergei Zuyev

Given a network, the statistical ensemble of its graph-Voronoi diagrams with randomly chosen cell centers exhibits properties convertible into information on the network's large scale structures. We define a node-pair level measure called…

This paper presents a novel approach to the analysis of spatial behavior distribution, utilizing weighted Voronoi diagrams. The objective is to map and understand how an experimental subject moves and spends time in various areas of a given…

Determinantal point processes are models for regular spatial point patterns, with appealing probabilistic properties. We present their spatio-temporal counterparts and give examples of these models, based on spatio-temporal covariance…

Statistics Theory · Mathematics 2023-01-09 Nafiseh Vafaei , Mohammad Ghorbani , Masoud Ganji , Mari Myllymäki

A new type of dependent thinning for point processes in continuous space is proposed, which leverages the advantages of determinantal point processes defined on finite spaces and, as such, is particularly amenable to statistical, numerical,…

Machine Learning · Computer Science 2019-06-19 Bartłomiej Błaszczyszyn , Paul Keeler

A novel algorithm to detect coherent structures with sparse Lagrangian particle tracking data, using Voronoi tessellation and techniques from spectral graph theory, is tested. Neighbouring tracer particles are naturally identified through…

Fluid Dynamics · Physics 2021-07-29 F. A. C. Martins , D. E. Rival

Voronoi Tessellations form an attractive and versatile geometrical asymptotic model for the foamlike cosmic distribution of matter and galaxies. In the Voronoi model the vertices are identified with clusters of galaxies. For a substantial…

Astrophysics · Physics 2007-05-23 Rien van de Weygaert

In this paper, we review the computational aspects of a multiscale dissipative particle dynamics model for complex fluid simulations based on the feature-rich geometry of the Voronoi tessellation. The geometrical features of the model are…

Soft Condensed Matter · Physics 2009-11-10 G. De Fabritiis , P. V. Coveney

Networks generated from Voronoi tessellations of space are prototypes for topologically disordered systems. In order to assess the effects of random coordination on the statistical properties of energy spectra, we analyze tight-binding…

Disordered Systems and Neural Networks · Physics 2017-09-27 Uwe Grimm , Rudolf A. Roemer , Gudrun Schliecker

This paper presents a range of results in partial differential equations (PDEs) in which Voronoi patterns arise. We investigate the connection between the solution to an elliptic equation and its probabilistic interpretation as a stochastic…

Analysis of PDEs · Mathematics 2023-02-28 Yuriria Cortes-Poza , David Padilla-Garza , Pablo Padilla

With our previous study, the Super-k algorithm, we have introduced a novel way of piecewise-linear classification. While working on the Super-k algorithm, we have found that there is a similar, and simpler way to explain for obtaining a…

Machine Learning · Computer Science 2021-02-03 Rahman Salim Zengin , Volkan Sezer

Machine learning techniques have been used to quantify the relationship between local structural features and variations in local dynamical activity in disordered glass-forming materials. To date these methods have been applied to an array…

Soft Condensed Matter · Physics 2021-01-07 Indrajit Tah , Tristan A. Sharp , Andrea J. Liu , Daniel M. Sussman

Since the Voronoi diagram appears in many applications, the topic of improving its computational efficiency remains attractive. We propose a novel yet efficient method to compute Voronoi diagrams bounded by a given domain, i.e., the clipped…

Graphics · Computer Science 2026-02-17 Yanyang Xiao , Juan Cao , Zhonggui Chen

Poisson Voronoi tessellations have been used in modeling many types of systems across different sciences, from geography and astronomy to telecommunications. The existing literature on the statistical properties of Poisson Voronoi cells is…

Networking and Internet Architecture · Computer Science 2020-09-09 Konstantinos Koufos , Carl P. Dettmann

We derive a mesoscopic modeling and simulation technique that is very close to the technique known as dissipative particle dynamics. The model is derived from molecular dynamics by means of a systematic coarse-graining procedure. Thus the…

Soft Condensed Matter · Physics 2009-10-31 Eirik G. Flekkoy , Peter V. Coveney , Gianni De Fabritiis

Cells of Voronoi diagrams in two dimensions are usually considered as having edges of zero width. However, this is not the case in several experimental situations in which the thickness of the edges of the cells is relatively large. In this…

Statistical Mechanics · Physics 2012-07-04 L. Zaninetti

We introduce an algorithm to estimate the redshift distribution of a sample of galaxies selected photometrically given a subsample with measured spectroscopic redshifts. The approach uses a non-parametric Voronoi tessellation density…

Cosmology and Nongalactic Astrophysics · Physics 2016-02-10 Benjamin R. Granett