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Generalised degrees provide a natural bridge between local and global topological properties of networks. We define the generalised degree to be the number of neighbours of a node within one and two steps respectively. Tailored random graph…

Disordered Systems and Neural Networks · Physics 2013-09-17 Ekaterina S. Roberts , Anthonius C. C. Coolen

There are several notions of convergence for sequences of bounded degree graphs. One such notion is left convergence, which is based on counting neighborhood distributions. Another notion is right convergence, based on counting…

Combinatorics · Mathematics 2015-05-12 László Miklós Lovász

The notions of bounded expansion and nowhere denseness not only offer robust and general definitions of uniform sparseness of graphs, they also describe the tractability boundary for several important algorithmic questions. In this paper we…

Discrete Mathematics · Computer Science 2019-09-25 Wojciech Nadara , Marcin Pilipczuk , Roman Rabinovich , Felix Reidl , Sebastian Siebertz

A \emph{locally irregular graph} is a graph whose adjacent vertices have distinct degrees. We say that a graph $G$ can be decomposed into $k$ locally irregular subgraphs if its edge set may be partitioned into $k$ subsets each of which…

Combinatorics · Mathematics 2017-03-02 Jakub Przybyło

We study symmetric motifs in random geometric graphs. Symmetric motifs are subsets of nodes which have the same adjacencies. These subgraphs are particularly prevalent in random geometric graphs and appear in the Laplacian and adjacency…

Disordered Systems and Neural Networks · Physics 2017-07-28 Carl P. Dettmann , Georgie Knight

The Lov\'asz Local Lemma is a powerful probabilistic technique for proving the existence of combinatorial objects. It is especially useful for colouring graphs and hypergraphs with bounded maximum degree. This paper presents a general…

Combinatorics · Mathematics 2021-04-14 Ian M. Wanless , David R. Wood

A growing set of on-line applications are generating data that can be viewed as very large collections of small, dense social graphs -- these range from sets of social groups, events, or collaboration projects to the vast collection of…

Social and Information Networks · Computer Science 2013-05-15 Johan Ugander , Lars Backstrom , Jon Kleinberg

For any countably infinite graph $G$, Ramsey's theorem guarantees an infinite monochromatic copy of $G$ in any $r$-coloring of the edges of the countably infinite complete graph $K_\mathbb{N}$. Taking this a step further, it is natural to…

Combinatorics · Mathematics 2018-08-16 Louis DeBiasio , Paul McKenney

We consider sequences of graphs and define various notions of convergence related to these sequences: ``left convergence'' defined in terms of the densities of homomorphisms from small graphs into the graphs of the sequence, and ``right…

Combinatorics · Mathematics 2007-05-23 C. Borgs , J. T. Chayes , L. Lovasz , V. T. Sos , K. Vesztergombi

We present a new approach to graph limit theory which unifies and generalizes the two most well developed directions, namely dense graph limits (even the more general $L^p$ limits) and Benjamini--Schramm limits (even in the stronger…

Combinatorics · Mathematics 2018-11-05 Agnes Backhausz , Balazs Szegedy

This paper proves limit theorems for the number of monochromatic edges in uniform random colorings of general random graphs. These can be seen as generalizations of the birthday problem (what is the chance that there are two friends with…

Probability · Mathematics 2018-02-13 Bhaswar B. Bhattacharya , Persi Diaconis , Sumit Mukherjee

We study which property testing and sublinear time algorithms can be transformed into graph streaming algorithms for random order streams. Our main result is that for bounded degree graphs, any property that is constant-query testable in…

Data Structures and Algorithms · Computer Science 2017-07-25 Morteza Monemizadeh , S. Muthukrishnan , Pan Peng , Christian Sohler

Subgraph densities play a crucial role in network analysis, especially for the identification and interpretation of meaningful substructures in complex graphs. Localized subgraph densities, in particular, can provide valuable insights into…

Social and Information Networks · Computer Science 2025-05-23 Connor Mattes , Esha Datta , Ali Pinar

We present a graph model for a background independent, relational approach to spacetime emergence. The general idea and the graph main features, detailed in [1], are discussed. This is a combinatorial (dynamical) metric graph, colored on…

General Relativity and Quantum Cosmology · Physics 2020-07-14 D. Pugliese

Various results ensure the existence of large complete bipartite graphs in properly colored graphs when some condition related to a topological lower bound on the chromatic number is satisfied. We generalize three theorems of this kind,…

Combinatorics · Mathematics 2017-04-04 Meysam Alishahi , Hossein Hajiabolhassan , Frédéric Meunier

In this paper, matching pairs of random graphs under the community structure model is considered. The problem emerges naturally in various applications such as privacy, image processing and DNA sequencing. A pair of randomly generated…

Cryptography and Security · Computer Science 2018-11-01 F. Shirani , S. Garg , E. Erkip

Colored tensor models (CTM) is a random geometrical approach to quantum gravity. We scrutinize the structure of the connected correlation functions of general CTM-interactions and organize them by boundaries of Feynman graphs. For rank-$D$…

Mathematical Physics · Physics 2020-02-05 Carlos I. Pérez-Sánchez

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…

We consider the problem of estimating graph limits, known as graphons, from observations of sequences of sparse finite graphs. In this paper we show a simple method that can shed light on a subset of sparse graphs. The method involves…

Machine Learning · Statistics 2025-07-08 Sevvandi Kandanaarachchi , Cheng Soon Ong

A powerful framework for studying graphs is to consider them as geometric graphs: nodes are randomly sampled from an underlying metric space, and any pair of nodes is connected if their distance is less than a specified neighborhood radius.…

Machine Learning · Computer Science 2022-11-28 Raffaele Paolino , Aleksandar Bojchevski , Stephan Günnemann , Gitta Kutyniok , Ron Levie