English
Related papers

Related papers: Random Tessellations -- An Overview of Models

200 papers

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

We make use of the recent proof that the critical probability for percolation on random Voronoi tessellations is 1/2 to prove the corresponding result for random Johnson-Mehl tessellations, as well as for two-dimensional slices of higher…

Probability · Mathematics 2010-02-06 Bela Bollobas , Oliver Riordan

Random graphs are more and more used for modeling real world networks such as evolutionary networks of proteins. For this purpose we look at two different models and analyze how properties like connectedness and degree distributions are…

Probability · Mathematics 2019-02-05 Klemens Taglieber , Uta Freiberg

Owing to the natural interpretation and various desirable mathematical properties, centroidal Voronoi tessellations (CVT) have found a wide range of applications and correspondingly a vast development in their literature. However the…

Computational Geometry · Computer Science 2022-03-30 Bhagyashri Telsang , Seddik Djouadi

Tessellations are valuable both conceptually and for analysis in the study of the large-scale structure of the universe. They provide a conceptual model for the 'cosmic web,' and are of great use to analyze cosmological data. Here we…

Cosmology and Nongalactic Astrophysics · Physics 2012-07-20 Mark C. Neyrinck , Sergei F. Shandarin

We present new stochastic geometry theorems that give bounds on the probability that $m$ random data classes all contain a point in common in their convex hulls. We apply these stochastic separation theorems to obtain bounds on the…

Probability · Mathematics 2019-07-24 Jesús A. De Loera , Thomas A. Hogan

High energy experimental data can be viewed as a sampling of the relevant phase space. We point out that one can apply Voronoi tessellations in order to understand the underlying probability distributions in this phase space. Interesting…

High Energy Physics - Phenomenology · Physics 2015-11-10 Dipsikha Debnath , James S. Gainer , Doojin Kim , Konstantin T. Matchev

We provide a self-contained introduction to random matrices. While some applications are mentioned, our main emphasis is on three different approaches to random matrix models: the Coulomb gas method and its interpretation in terms of…

Mathematical Physics · Physics 2018-07-06 Bertrand Eynard , Taro Kimura , Sylvain Ribault

Random matrix models encode a theory of random two dimensional surfaces with applications to string theory, conformal field theory, statistical physics in random geometry and quantum gravity in two dimensions. The key to their success lies…

Mathematical Physics · Physics 2012-09-21 Razvan Gurau

We review a collection of models of random simplicial complexes together with some of the most exciting phenomena related to them. We do not attempt to cover all existing models, but try to focus on those for which many important results…

Probability · Mathematics 2022-05-04 Omer Bobrowski , Dmitri Krioukov

Networks are a commonly used mathematical model to describe the rich set of interactions between objects of interest. Many clustering methods have been developed in order to partition such structures, among which several rely on underlying…

Methodology · Statistics 2014-05-13 P. Latouche , E. Birmelé , C. Ambroise

A branching random tessellation (BRT) is a stochastic process that transforms a coarse initial tessellation of $\mathbb{R}^d$ into a finer tessellation by means of random cell divisions in continuous time. This concept generalises the…

Probability · Mathematics 2015-09-10 Hans-Otto Georgii , Tomasz Schreiber , Christoph Thäle

An analogue of the classical Mecke formula for Poisson point processes is proved for the class of space-time STIT tessellation processes. From this key identity the Markov property of a class of associated random processes is derived. This…

Probability · Mathematics 2017-11-06 Werner Nagel , Linh Ngoc Nguyen , Christoph Thaele , Viola Weiss

One can see deep-learning models as compositions of functions within the so-called tame geometry. In this expository note, we give an overview of some topics at the interface of tame geometry (also known as o-minimality), optimization…

Optimization and Control · Mathematics 2025-09-23 Gilles Bareilles , Allen Gehret , Johannes Aspman , Jana Lepšová , Jakub Mareček

We introduce a framework for the generation of grid-shell structures that is based on Voronoi diagrams and allows us to design tessellations that achieve excellent static performances. We start from an analysis of stress on the input…

Graphics · Computer Science 2014-08-29 Nico Pietroni , Davide Tonelli , Enrico Puppo , Maurizio Froli , Roberto Scopigno , Paolo Cignoni

We present a selective review on probabilistic modeling of heterogeneity in random graphs. We focus on latent space models and more particularly on stochastic block models and their extensions that have undergone major developments in the…

Statistics Theory · Mathematics 2014-09-26 Catherine Matias , Stéphane Robin

Random Wavelet Series form a class of random processes with multifractal properties. We give three applications of this construction. First, we synthesize a random function having any given spectrum of singularities satisfying some…

Mathematical Physics · Physics 2007-05-23 Jean-Marie Aubry , Stéphane Jaffard

A random planar quadrangulation process is introduced as an approximation for certain cellular automata in terms of random growth of rays from a given set of points. This model turns out to be a particular (rectangular) case of the…

Probability · Mathematics 2025-10-17 Emily Ewers , Tatyana Turova

Statistical models that possess symmetry arise in diverse settings such as random fields associated to geophysical phenomena, exchangeable processes in Bayesian statistics, and cyclostationary processes in engineering. We formalize the…

Statistics Theory · Mathematics 2011-12-01 Parikshit Shah , Venkat Chandrasekaran

We introduce the notion of a stochastic probabilistic program and present a reference implementation of a probabilistic programming facility supporting specification of stochastic probabilistic programs and inference in them. Stochastic…

Machine Learning · Statistics 2020-01-23 David Tolpin , Tomer Dobkin
‹ Prev 1 4 5 6 7 8 10 Next ›