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Related papers: Infinite random graphs

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Because of the huge number of graphs possible even with a small number of nodes, inference on network structure is known to be a challenging problem. Generating large random directed graphs with prescribed probabilities of occurrences of…

Quantitative Methods · Quantitative Biology 2017-05-03 Frederic Y. Bois , Ghislaine Gayraud

Random graph models have played a dominant role in the theoretical study of networked systems. The Poisson random graph of Erdos and Renyi, in particular, as well as the so-called configuration model, have served as the starting point for…

Statistical Mechanics · Physics 2014-12-03 M. E. J. Newman , Travis Martin

The literature on word-representable graphs is quite rich, and a number of variations of the original definition have been proposed over the years. We are initiating a systematic study of such variations based on formal languages. In our…

Discrete Mathematics · Computer Science 2024-11-06 Zhidan Feng , Henning Fernau , Pamela Fleischmann , Kevin Mann , Silas Cato Sacher

Graph compositions generalize both integer compositions and partitions of a finite set. We develop formulas, generating functions and recurrence relations for composition counting functions for several families of graphs.

Combinatorics · Mathematics 2007-05-23 A Knopfmacher , M E Mays

Graph-structured data arise in wide applications, such as computer vision, bioinformatics, and social networks. Quantifying similarities among graphs is a fundamental problem. In this paper, we develop a framework for computing graph…

Machine Learning · Statistics 2018-09-11 Zhen Zhang , Mianzhi Wang , Yijian Xiang , Yan Huang , Arye Nehorai

In this paper we investigate families of connected graphs which do not contain an odd cycle in their complement. Specifically, we consider graphs formed by two complete graphs connected in a particular way. We determine which of these…

Group Theory · Mathematics 2020-08-27 Jacob Laubacher , Mark Medwid

Random graph models are frequently used as a controllable and versatile data source for experimental campaigns in various research fields. Generating such data-sets at scale is a non-trivial task as it requires design decisions typically…

Data Structures and Algorithms · Computer Science 2020-03-03 Manuel Penschuck , Ulrik Brandes , Michael Hamann , Sebastian Lamm , Ulrich Meyer , Ilya Safro , Peter Sanders , Christian Schulz

We propose and investigate a unifying class of sparse random graph models, based on a hidden coloring of edge-vertex incidences, extending an existing approach, Random graphs with a given degree distribution, in a way that admits a…

Statistical Mechanics · Physics 2009-11-10 Bo Söderberg

A set of graphs is said to be independent if there is no homomorphism between distinct graphs from the set. We consider the existence problems related to the independent sets of countable graphs. While the maximal size of an independent set…

Logic · Mathematics 2007-05-23 Jaroslav Nešetřil , Saharon Shelah

We determine to within a constant factor the threshold for the property that two random k-uniform hypergraphs with edge probability p have an edge-disjoint packing into the same vertex set. More generally, we allow the hypergraphs to have…

Combinatorics · Mathematics 2016-03-01 Béla Bollobás , Svante Janson , Alex Scott

Given a countable graph, we say a set $A$ of its vertices is \emph{universal} if it contains every countable graph as an induced subgraph, and $A$ is \emph{weakly universal} if it contains every finite graph as an induced subgraph. We show…

Combinatorics · Mathematics 2017-02-24 Will Brian

We give sufficient conditions under which a random graph with a specified degree sequence is symmetric or asymmetric. In the case of bounded degree sequences, our characterisation captures the phase transition of the symmetry of the random…

Combinatorics · Mathematics 2020-04-07 Lochlan Brick , Pu Gao , Angus Southwell

This work will appear as a chapter in a forthcoming volume titled "Topics in Probabilistic Graph Theory". A theory of scaling limits for random graphs has been developed in recent years. This theory gives access to the large-scale geometric…

Probability · Mathematics 2024-10-18 Louigi Addario-Berry , Christina Goldschmidt

We perform a massive evaluation of neural networks with architectures corresponding to random graphs of various types. We investigate various structural and numerical properties of the graphs in relation to neural network test accuracy. We…

Machine Learning · Computer Science 2020-12-03 Romuald A. Janik , Aleksandra Nowak

We introduce a new notation for representing labeled regular bipartite graphs of arbitrary degree. Several enumeration problems for labeled and unlabeled regular bipartite graphs have been introduced. A general algorithm for enumerating all…

Discrete Mathematics · Computer Science 2015-12-31 Vivek S. Nittoor

Suppose we are given two graphs on $n$ vertices. We define an observable in the Hilbert space $\Co[(S_n \wr S_2)^m]$ which returns the answer ``yes'' with certainty if the graphs are isomorphic and ``no'' with probability at least…

Quantum Physics · Physics 2007-05-23 Mark Ettinger , Peter Hoyer

We show that the only random orderings of finite graphs that are invariant under isomorphism and induced subgraph are the uniform random orderings. We show how this implies the unique ergodicity of the automorphism group of the random…

Dynamical Systems · Mathematics 2018-09-10 Omer Angel , Alexander S. Kechris , Russell Lyons

Many real-world networks of interest are embedded in physical space. We present a new random graph model aiming to reflect the interplay between the geometries of the graph and of the underlying space. The model favors configurations with…

Probability · Mathematics 2017-06-14 Jean-Christophe Mourrat , Daniel Valesin

We focus on the algorithm underlying the main result of [A. Mestre, R. Oeckl, Generating loop graphs via Hopf algebra in quantum field theory. J. Math. Phys., 47, 122302, 2006]. This is an algebraic formula to generate all connected graphs…

Combinatorics · Mathematics 2013-03-14 Angela Mestre

The unconstrained exponential family of random graphs assumes no prior knowledge of the graph before sampling, but it is natural to consider situations where partial information about the graph is known, for example the total number of…

Probability · Mathematics 2017-04-19 Richard Kenyon , Mei Yin