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Much attention has recently been devoted to data-based computing of evolution of physical systems. In such approaches, information about data points from past trajectories in phase space is used to reconstruct the equations of motion and to…

Machine Learning · Computer Science 2026-03-24 Christopher Eldred , François Gay-Balmaz , Vakhtang Putkaradze

Since the seminal work by Nagel and Weiss, the iteration stable (STIT) tessellations have attracted considerable interest in stochastic geometry as a natural and flexible, yet analytically tractable model for hierarchical spatial…

Probability · Mathematics 2014-12-25 Tomasz Schreiber , Christoph Thaele

Color image segmentation is a crucial step in many computer vision and pattern recognition applications. This article introduces an adaptive and unsupervised clustering approach based on Voronoi regions, which can be applied to solve the…

Computer Vision and Pattern Recognition · Computer Science 2016-04-05 R. Hettiarachchi , J. F. Peters

We show that real model sets with real internal spaces are determined, up to translation and changes of density zero by their two- and three-point correlations. We also show that there exist pairs of real (even one dimensional) aperiodic…

Mathematical Physics · Physics 2015-05-13 Xinghua Deng , Robert V. Moody

Point cloud sequences are irregular and unordered in the spatial dimension while exhibiting regularities and order in the temporal dimension. Therefore, existing grid based convolutions for conventional video processing cannot be directly…

Computer Vision and Pattern Recognition · Computer Science 2022-05-30 Hehe Fan , Xin Yu , Yuhang Ding , Yi Yang , Mohan Kankanhalli

We define a new variant of exclusion processes in discrete time that has jump probabilities that depend on the last jump performed. In a particular limit for the jump probabilities and in suitable scaling limits for space and time, we…

Statistical Mechanics · Physics 2021-04-01 Bryan Debin , Etienne Granet

Spatiotemporal point processes (STPPs) are probabilistic models for events occurring in continuous space and time. Real-world event data often exhibit intricate dependencies and heterogeneous dynamics. By incorporating modern deep learning…

Machine Learning · Computer Science 2025-02-14 Sumantrak Mukherjee , Mouad Elhamdi , George Mohler , David A. Selby , Yao Xie , Sebastian Vollmer , Gerrit Grossmann

We investigate spatio-temporal event analysis using point processes. Inferring the dynamics of event sequences spatiotemporally has many practical applications including crime prediction, social media analysis, and traffic forecasting. In…

Machine Learning · Computer Science 2021-02-17 Fatih Ilhan , Suleyman Serdar Kozat

We study the sizes of the Voronoi cells of $k$ uniformly chosen vertices in a random split tree of size $n$. We prove that, for $n$ large, the largest of these $k$ Voronoi cells contains most of the vertices, while the sizes of the…

Probability · Mathematics 2021-03-18 Alexander Drewitz , Markus Heydenreich , Cécile Mailler

For a group of pedestrians without any spatial boundaries, the methods of density estimation is a wide area of research. Besides, there is a specific difficulty when the density along one given pedestrian trajectory is needed in order to…

Physics and Society · Physics 2024-11-06 Pratik Mullick , Cécile Appert-Rolland , William H. Warren , Julien Pettré

We study a class of discrete models in which a collection of particles evolves in time following the gradient flow of an energy depending on the cell areas of an associated Laguerre (i.e. a weighted Voronoi) tessellation. We consider the…

Numerical Analysis · Mathematics 2025-04-01 Andrea Natale

We use a Voronoi-type tessellation based on a compound Poisson point process to construct a polynomially mixing stationary random smooth planar vector field with bounded nonnegative components such that, with probability one, none of the…

Dynamical Systems · Mathematics 2022-11-17 Yuri Bakhtin , Liying Li

A key process in the life of any multicellular organism is its development from a single egg into a full grown adult. The first step in this process often consists of forming a tissue layer out of randomly placed cells on the surface of the…

When analyzing data from multiple sources, it is often convenient to strike a careful balance between two goals: capturing the heterogeneity of the samples and sharing information across them. We introduce a novel framework to model a…

Methodology · Statistics 2026-03-02 Laura D'Angelo , Bernardo Nipoti , Andrea Ongaro

Let $(M_t: t > 0)$ be a Markov process of tessellations of ${\mathbb R}^\ell$ and $({\cal C}_t:\, t > 0)$ the process of their zero cells (zero polytopes) which has the same distribution as the corresponding process for Poisson hyperplane…

Probability · Mathematics 2026-01-14 Servet Martínez , Werner Nagel

Let N, N' and N'' be point processes such that N' is obtained from N by homogeneous independent thinning and N''= N- N'. We give a new elementary proof that N' and N'' are independent if and only if N is a Poisson point process. We present…

Probability · Mathematics 2011-11-10 Renato M. Assuncao , Pablo A. Ferrari

We study percolation in the following random environment: let $Z$ be a Poisson process of constant intensity in the plane, and form the Voronoi tessellation of the plane with respect to $Z$. Colour each Voronoi cell black with probability…

Probability · Mathematics 2007-05-23 Bela Bollobas , Oliver Riordan

In this work, we study a new model for continuum line-of-sight percolation in a random environment driven by the Poisson-Voronoi tessellation in the $d$-dimensional Euclidean space. The edges (one-dimensional facets, or simply 1-facets) of…

Probability · Mathematics 2020-11-10 Quentin Le Gall , Bartłomiej Błaszczyszyn , Elie Cali , Taoufik En-Najjary

In this article, using kernel convolution of order based dependent Dirichlet process (Griffin and Steel (2006)) we construct a nonstationary, nonseparable, nonparametric space-time process, which, as we show, satisfies desirable properties,…

Methodology · Statistics 2020-05-04 Moumita Das , Sourabh Bhattacharya

Numerical simulations of the air in the atmosphere and water in the oceans are essential for numerical weather prediction. The state-of-the-art for performing these fluid simulations relies on an Eulerian viewpoint, in which the fluid…

Fluid Dynamics · Physics 2025-08-12 Philip Caplan , Otis Milliken , Toby Pouler , Zeyi Tong , Col McDermott , Sam Millay
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