We introduce a model for a growing random graph based on simultaneous reproduction of the vertices. The model can be thought of as a generalisation of the reproducing graphs of Southwell and Cannings and Bonato et al to allow for a random element, and there are three parameters, alpha, beta and gamma, which are the probabilities of edges appearing between different types of vertices. We show that as the probabilities associated with the model vary there are a number of phase transitions, in particular concerning the degree sequence. If (1 + alpha) (1 + gamma) 1 then the degree of a typical vertex grows to infinity, and the proportion of vertices having any fixed degree d tends to zero. We also give some results on the number of edges and o...
Volchenkov D, Blanchard P. An algorithm generating random graphs with power law degree distributions...
The classical random graph models, in particular G(n,p), are homogeneous, in the sense that the ...
Consider the following modification of the Barabási–Albert random graph. At every step a new vertex...
We deal with a random graph model where at each step, a vertex is chosen uniformly at random, and it...
We consider a preferential duplication model for growing random graphs, extending previous models of...
We introduce a process where a connected rooted multigraph evolves by splitting events on its vertic...
Random graphs is a well-studied field of probability theory, and have proven very useful in a range ...
We deal with a random graph model evolving in discrete time steps by duplicating and deleting the ed...
In this thesis we consider models of random graphs where, unlike in the classical models G (n, p) t...
In a 2-parameter scale free model of random graphs it is shown that the asymptotic degree distributi...
In this paper, we introduce variations on random graph models for Web-like graphs. As a basis, we re...
We introduce general models of evolving, inhomogeneous random structures, where in each of the model...
In this book, we study random graphs as models for real-world networks. Since 1999, many real-world ...
A Markov chain approach to the study of randomly grown graphs is proposed and applied to some popula...
AbstractThis paper focuses on the degree sequence of a random graph process with copying and vertex ...
Volchenkov D, Blanchard P. An algorithm generating random graphs with power law degree distributions...
The classical random graph models, in particular G(n,p), are homogeneous, in the sense that the ...
Consider the following modification of the Barabási–Albert random graph. At every step a new vertex...
We deal with a random graph model where at each step, a vertex is chosen uniformly at random, and it...
We consider a preferential duplication model for growing random graphs, extending previous models of...
We introduce a process where a connected rooted multigraph evolves by splitting events on its vertic...
Random graphs is a well-studied field of probability theory, and have proven very useful in a range ...
We deal with a random graph model evolving in discrete time steps by duplicating and deleting the ed...
In this thesis we consider models of random graphs where, unlike in the classical models G (n, p) t...
In a 2-parameter scale free model of random graphs it is shown that the asymptotic degree distributi...
In this paper, we introduce variations on random graph models for Web-like graphs. As a basis, we re...
We introduce general models of evolving, inhomogeneous random structures, where in each of the model...
In this book, we study random graphs as models for real-world networks. Since 1999, many real-world ...
A Markov chain approach to the study of randomly grown graphs is proposed and applied to some popula...
AbstractThis paper focuses on the degree sequence of a random graph process with copying and vertex ...
Volchenkov D, Blanchard P. An algorithm generating random graphs with power law degree distributions...
The classical random graph models, in particular G(n,p), are homogeneous, in the sense that the ...
Consider the following modification of the Barabási–Albert random graph. At every step a new vertex...