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We introduce probability-graphons which are probability kernels that generalize graphons to the case of weighted graphs. Probability-graphons appear as the limit objects to study sequences of large weighted graphs whose distribution of…

Discrete Mathematics · Computer Science 2025-06-12 Romain Abraham , Jean-François Delmas , Julien Weibel

A {\em faithful (unit) distance graph} in $\mathbb{R}^d$ is a graph whose set of vertices is a finite subset of the $d$-dimensional Euclidean space, where two vertices are adjacent if and only if the Euclidean distance between them is…

Combinatorics · Mathematics 2017-12-01 Noga Alon , Andrey Kupavskii

The problem of continuum percolation in dispersions of rods is reformulated in terms of weighted random geometric graphs. Nodes (or sites or vertices) in the graph represent spatial locations occupied by the centers of the rods. The…

Statistical Mechanics · Physics 2015-09-30 Avik P. Chatterjee , Claudio Grimaldi

Let $X_1,X_2,...$ be an infinite sequence of i.i.d. random vectors distributed exponentially with parameter $\lam .$ For each $y$ and $n\geq 1,$ form a graph $G_n(y)$ with vertex set $V_n = \{X_1,...,X_n\},$ two vertices are connected if…

Probability · Mathematics 2007-05-23 Bhupendra Gupta

Rank 1 inhomogeneous random graphs are a natural generalization of Erd\H{o}s R\'enyi random graphs. In this generalization each node is given a weight. Then the probability that an edge is present depends on the product of the weights of…

Probability · Mathematics 2021-07-28 Othmane Safsafi

Consider a random geometric graph over a random point process in $\mathbb{R}^d$. Two points are connected by an edge if and only if their distance is bounded by a prescribed distance parameter. We show that projecting the graph onto a two…

Discrete Mathematics · Computer Science 2020-08-26 Markus Chimani , Hanna Döring , Matthias Reitzner

Curvature is a fundamental geometric characteristic of smooth spaces. In recent years different notions of curvature have been developed for combinatorial discrete objects such as graphs. However, the connections between such discrete…

Probability · Mathematics 2023-11-09 Pim van der Hoorn , Gabor Lippner , Carlo Trugenberger , Dmitri Krioukov

The semi-random graph process is a single-player game that begins with an empty graph on $n$ vertices. In each round, a vertex $u$ is presented to the player independently and uniformly at random. The player then adaptively selects a vertex…

Combinatorics · Mathematics 2024-03-05 Natalie C. Behague , Trent G. Marbach , Pawel Pralat , Andrzej Rucinski

We conduct a quantitative analysis of how many random edges need to be added to a base graph $H$ in order to significantly increase natural minor-monotone graph parameters of the resulting graph $R$. Specifically, we show that if $R$ is…

Combinatorics · Mathematics 2026-01-16 Dong Yeap Kang , Mihyun Kang , Jaehoon Kim , Sang-il Oum

We consider isomorphism properties of infinite random geometric graphs defined over a variety of metrics. In previous work, it was shown that for $\mathbb{R}^n$ with the $L_{\infty}$-metric, the infinite random geometric graph is, with…

Combinatorics · Mathematics 2014-08-12 Anthony Bonato , Jeannette Janssen

A crossing-free straight-line drawing of a graph is monotone if there is a monotone path between any pair of vertices with respect to some direction. We show how to construct a monotone drawing of a tree with $n$ vertices on an $O(n^{1.5})…

Computational Geometry · Computer Science 2016-04-26 Philipp Kindermann , André Schulz , Joachim Spoerhase , Alexander Wolff

We study the connectivity properties of random Bluetooth graphs that model certain "ad hoc" wireless networks. The graphs are obtained as "irrigation subgraphs" of the well-known random geometric graph model. There are two parameters that…

Probability · Mathematics 2011-03-03 Nicolas Broutin , Luc Devroye , Nicolas Fraiman , Gábor Lugosi

We study geometric random graphs defined on the points of a Poisson process in $d$-dimensional space, which additionally carry independent random marks. Edges are established at random using the marks of the endpoints and the distance…

Probability · Mathematics 2022-08-10 Peter Gracar , Arne Grauer , Peter Mörters

A rigidity theory is developed for the Euclidean and non-Euclidean placements of countably infinite simple graphs in R^d with respect to the classical l^p norms, for d>1 and 1<p<\infty. Generalisations are obtained for the Laman and…

Metric Geometry · Mathematics 2013-10-08 D. Kitson , S. C. Power

The dissertation is related to combinatorial geometry with a strong probabilistic flavor. The main results can be split into three parts. The results of the first part guarantee that each "unit distance graph" in the plane has an induced…

Combinatorics · Mathematics 2015-01-16 Andrei A. Kokotkin

We consider uniform random cographs (either labeled or unlabeled) of large size. Our first main result is the convergence towards a Brownian limiting object in the space of graphons. We then show that the degree of a uniform random vertex…

In this work, we develop a unified framework for establishing sharp threshold results for various Ramsey properties. To achieve this, we view such properties as non-colourability of auxiliary hypergraphs. Our main technical result gives…

Combinatorics · Mathematics 2026-03-04 Ehud Friedgut , Eden Kuperwasser , Wojciech Samotij , Mathias Schacht

Consider the binomial model $G^{d+1}(n,p)$ of the random $(d+1)$-uniform hypergraph on $n$ vertices, where each edge is present, independently of one another, with probability $p:\mathbb{N}\to[0,1]$. We prove that, for all…

Combinatorics · Mathematics 2016-02-23 Nicolau C. Saldanha , Márcio Telles

Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina

Graph neural networks (GNNs) are powerful machine learning models for various graph learning tasks. Recently, the limitations of the expressive power of various GNN models have been revealed. For example, GNNs cannot distinguish some…

Machine Learning · Computer Science 2021-01-19 Ryoma Sato , Makoto Yamada , Hisashi Kashima
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