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We introduce a very general model of an inhomogenous random graph with independence between the edges, which scales so that the number of edges is linear in the number of vertices. This scaling corresponds to the p=c/n scaling for G(n,p)…

Probability · Mathematics 2011-11-10 Bela Bollobas , Svante Janson , Oliver Riordan

A random graph order is a partial order achieved by independently sprinkling relations on a vertex set (each with probability $p$) and adding relations to satisfy the requirement of transitivity. A \textit{post} is an element in a partially…

Combinatorics · Mathematics 2008-09-25 Luca Bombelli , Itai Seggev , Sam Watson

We propose two models of social segregation inspired by the Schelling model. Agents in our models are nodes of evolving social networks. The total number of social connections of each node remains constant in time, though may vary from one…

Physics and Society · Physics 2018-09-26 V. Avetisov , A. Gorsky , S. Maslov , S. Nechaev , O. Valba

A subgraph of an edge-colored graph is called \emph{rainbow} if all of its edges have distinct colors. There has been much research on the topic of finding a large rainbow matching in a properly edge-colored graph, where a proper…

Combinatorics · Mathematics 2026-05-28 Debsoumya Chakraborti , Po-Shen Loh

In a graph $G$ with a given edge colouring, a rainbow path is a path all of whose edges have distinct colours. The minimum number of colours required to colour the edges of $G$ so that every pair of vertices is joined by at least one…

Combinatorics · Mathematics 2012-12-10 Annika Heckel , Oliver Riordan

Zero forcing is a deterministic iterative graph coloring process in which vertices are colored either blue or white, and in every round, any blue vertices that have a single white neighbor force these white vertices to become blue. Here we…

Combinatorics · Mathematics 2019-09-17 Sean English , Calum MacRury , Pawel Pralat

In a coalescing random walk, a set of particles make independent random walks on a graph. Whenever one or more particles meet at a vertex, they unite to form a single particle, which then continues the random walk through the graph.…

Data Structures and Algorithms · Computer Science 2016-12-28 Colin Cooper , Robert Elsasser , Hirotaka Ono , Tomasz Radzik

An ordered graph is a graph with a linear ordering on its vertices. The online Ramsey game for ordered graphs $G$ and $H$ is played on an infinite sequence of vertices; on each turn, Builder draws an edge between two vertices, and Painter…

Combinatorics · Mathematics 2024-03-29 Felix Christian Clemen , Emily Heath , Mikhail Lavrov

An edge colored graph $G$ is rainbow edge connected if any two vertices are connected by a path whose edges have distinct colors. The rainbow connection of a connected graph $G$, denoted by $rc(G)$, is the smallest number of colors that are…

Combinatorics · Mathematics 2014-12-03 Andrzej Dudek , Alan Frieze , Charalampos Tsourakakis

One of the most famous results in the theory of random graphs establishes that the threshold for Hamiltonicity in the Erdos-Renyi random graph G_{n,p} is around p ~ (log n + log log n) / n. Much research has been done to extend this to…

Combinatorics · Mathematics 2011-01-04 Alan Frieze , Po-Shen Loh

We study a variation of the graph colouring problem on random graphs of finite average connectivity. Given the number of colours, we aim to maximise the number of different colours at neighbouring vertices (i.e. one edge distance) of any…

Statistical Mechanics · Physics 2009-11-11 S. Bounkong , J. van Mourik , D. Saad

Majority dynamics on the binomial Erd\H{o}s-R\'enyi graph $\mathsf{G}(n,p)$ with $p=\lambda/\sqrt{n}$ is studied. In this process, each vertex has a state in $\{0,1\}$ and at each round, every vertex adopts the state of the majority of its…

Data Structures and Algorithms · Computer Science 2022-10-14 Ran Tamir

For a given $\delta \in (0,1)$, the randomly perturbed graph model is defined as the union of any $n$-vertex graph $G_0$ with minimum degree $\delta n$ and the binomial random graph $\mathbf{G}(n,p)$ on the same vertex set. Moreover, we say…

Combinatorics · Mathematics 2025-11-10 Kyriakos Katsamaktsis , Shoham Letzter , Amedeo Sgueglia

For a fixed graph $H$, what is the smallest number of colours $C$ such that there is a proper edge-colouring of the complete graph $K_n$ with $C$ colours containing no two vertex-disjoint colour-isomorphic copies, or repeats, of $H$? We…

Combinatorics · Mathematics 2021-06-28 David Conlon , Mykhaylo Tyomkyn

How does the chromatic number of a graph chosen uniformly at random from all graphs on $n$ vertices behave? This quantity is a random variable, so one can ask (i) for upper and lower bounds on its typical values, and (ii) for bounds on how…

Combinatorics · Mathematics 2023-08-21 Annika Heckel , Oliver Riordan

Statistical inference for exponential-family models of random graphs with dependent edges is challenging. We stress the importance of additional structure and show that additional structure facilitates statistical inference. A simple…

Statistics Theory · Mathematics 2020-03-13 Michael Schweinberger , Jonathan Stewart

An $(m,n)$-colored mixed graph $G$ is a graph with its arcs having one of the $m$ different colors and edges having one of the $n$ different colors. A homomorphism $f$ of an $(m,n)$-colored mixed graph $G$ to an $(m,n)$-colored mixed graph…

Discrete Mathematics · Computer Science 2015-08-31 Sandip Das , Soumen Nandi , Sagnik Sen

We analyze graph smoothing with \emph{mean aggregation}, where each node successively receives the average of the features of its neighbors. Indeed, it has quickly been observed that Graph Neural Networks (GNNs), which generally follow some…

Machine Learning · Statistics 2022-10-11 Nicolas Keriven

Distributed vertex coloring is one of the classic problems and probably also the most widely studied problems in the area of distributed graph algorithms. We present a new randomized distributed vertex coloring algorithm for the standard…

Data Structures and Algorithms · Computer Science 2021-04-13 Magnús M. Halldórsson , Fabian Kuhn , Yannic Maus , Tigran Tonoyan

Consistency models (CMs) are a powerful class of diffusion-based generative models optimized for fast sampling. Most existing CMs are trained using discretized timesteps, which introduce additional hyperparameters and are prone to…

Machine Learning · Computer Science 2025-03-04 Cheng Lu , Yang Song