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In this paper, we present a novel approach based on the random walk process for finding meaningful representations of a graph model. Our approach leverages the transient behavior of many short random walks with novel initialization…

Social and Information Networks · Computer Science 2018-05-14 Lin Li , William M. Campbell , Rajmonda S. Caceres

We present and investigate an extension of the classical random graph to a general class of inhomogeneous random graph models, where vertices come in different types, and the probability of realizing an edge depends on the types of its…

Statistical Mechanics · Physics 2009-11-07 Bo Soderberg

This contribution proposes a new approach towards developing a class of probabilistic methods for classifying attributed graphs. The key concept is random attributed graph, which is defined as an attributed graph whose nodes and edges are…

Computer Vision and Pattern Recognition · Computer Science 2011-09-23 S. Deepak Srinivasan , Klaus Obermayer

We consider random walks on edge coloured random graphs, where the colour of an edge reflects the cost of using it. In the simplest instance, the edges are coloured red or blue. Blue edges are free to use, whereas red edges incur a unit…

Combinatorics · Mathematics 2025-08-28 Colin Cooper , Alan Frieze

A random intersection graph is constructed by assigning independently to each vertex a subset of a given set and drawing an edge between two vertices if and only if their respective subsets intersect. In this paper a model is developed in…

Probability · Mathematics 2015-09-24 Maria Deijfen , Willemien Kets

For an ordered set $W=\{w_1,w_2,...,w_k\}$ of vertices and a vertex $v$ in a connected graph $G$, the ordered $k$-vector $r(v|W):=(d(v,w_1),d(v,w_2),...,d(v,w_k))$ is called the (metric) representation of $v$ with respect to $W$, where…

Combinatorics · Mathematics 2011-03-17 Mohsen Jannesari , Behnaz Omoomi

Random recursive hypergraphs grow by adding, at each step, a vertex and an edge formed by joining the new vertex to a randomly chosen existing edge. The model is parameter-free, and several characteristics of emerging hypergraphs admit neat…

Combinatorics · Mathematics 2026-01-23 P. L. Krapivsky

We study the intersection of a random geometric graph with an Erd\H{o}s-R\'enyi graph. Specifically, we generate the random geometric graph $G(n, r)$ by choosing $n$ points uniformly at random from $D=[0, 1]^2$ and joining any two points…

Combinatorics · Mathematics 2024-11-08 Patrick Bennett , Alan Frieze , Wesley Pegden

In this paper we will provide an introductory understanding of random graph models, and matchings in the case of Erdos-Renyi random graphs. We will provide a synthesis of background theory to this end. We will further examine pertinent…

Statistics Theory · Mathematics 2019-11-18 Lucas Rooney

We consider Gallai's graph Modular Decomposition theory for network analytics. On the one hand, by arguing that this is a choice tool for understanding structural and functional similarities among nodes in a network. On the other, by…

Discrete Mathematics · Computer Science 2018-12-04 Carenne Ludena , Miguel mendez , Nicolas Bolivar

The theory of colorful graphs can be developed by working in Galois field modulo (p), p > 2 and a prime number. The paper proposes a program of possible conversion of graph theory into a pleasant colorful appearance. We propose to paint the…

General Mathematics · Mathematics 2007-05-23 Dhananjay P. Mehendale

In this paper it is shown that it is possible to associate several polynomial ideals to a directed graph $D$ in order to find properties of it. In fact by using algebraic tools it is possible to give appropriate procedures for automatic…

Commutative Algebra · Mathematics 2007-05-23 Giuseppa Carrá Ferro , Daniela Ferrarello

Despite recent advancements in single-domain or single-object image generation, it is still challenging to generate complex scenes containing diverse, multiple objects and their interactions. Scene graphs, composed of nodes as objects and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-13 Sarthak Garg , Helisa Dhamo , Azade Farshad , Sabrina Musatian , Nassir Navab , Federico Tombari

Network motifs are characteristic patterns which occur in the networks essentially more frequently than the other patterns. For five motifs found in S. Itzkovitz, U. Alon, Phys. Rev.~E, 2005, 71, 026117-1, hierarchical random graphs are…

Mathematical Physics · Physics 2015-04-02 Monika Kotorowicz , Yuri Kozitsky

Specify a randomized algorithm that, given a very large graph or network, extracts a random subgraph. What can we learn about the input graph from a single subsample? We derive laws of large numbers for the sampler output, by relating…

Statistics Theory · Mathematics 2017-10-13 Peter Orbanz

We present a family of networks, expanded deterministic Apollonian networks, which are a generalization of the Apollonian networks and are simultaneously scale-free, small-world, and highly clustered. We introduce a labeling of their…

Physics and Society · Physics 2011-11-09 Zhongzhi Zhang , Francesc Comellas , Guillaume Fertin , André Raspaud , Lili Rong , Shuigeng Zhou

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 present a new and powerful algebraic framework for graph rewriting, based on drags, a class of graphs enjoying a novel composition operator. Graphs are embellished with roots and sprouts, which can be wired together to form edges. Drags…

Logic in Computer Science · Computer Science 2024-06-28 Nachum Dershowitz , Jean-Pierre Jouannaud , Fernando Orejas

A circulant graph H is defined on the set of vertices V=\left\{ 1,\ldots,n\right\} and edges E=\left\{ \left(i,j\right):\left|i-j\right|\equiv s\left(\textrm{mod}n\right),s\in S\right\} , where S\subseteq\left\{…

Combinatorics · Mathematics 2017-07-17 Sebastian Richter , Israel Rocha

Graphs are often used to organize data because of their simple topological structure, and therefore play a key role in machine learning. And it turns out that the low-dimensional embedded representation obtained by graph representation…

Machine Learning · Computer Science 2021-01-05 Xing Li , Wei Wei , Xiangnan Feng , Zhiming Zheng
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