There is a well-known connection between hypergraphs and bipartite graphs, obtained by treating the incidence matrix of the hypergraph as the biadjacency matrix of a bipartite graph. We use this connection to describe and analyse a rejection sampling algorithm for sampling simple uniform hypergraphs with a given degree sequence. Our algorithm uses, as a black box, an algorithm for sampling bipartite graphs with given degrees, uniformly or nearly uniformly, in (expected) polynomial time. The expected runtime of the hypergraph sampling algorithm depends on the (expected) runtime of the bipartite graph sampling algorithm , and the probability that a uniformly random bipartite graph with given degrees corresponds to a simple hypergraph. We give...
Many applications require randomly sampling bipartite graphs with fixed degrees, or randomly samplin...
AbstractAn algorithm is presented which randomly selects a labelled graph with specified vertex degr...
Many real-world networks exhibit correlations between the node degrees. For instance, in social netw...
There is a well-known connection between hypergraphs and bipartite graphs, obtained by treating the ...
There is a well-known connection between hypergraphs and bipartite graphs, obtained by treating the ...
Graphs are combinatorial objects commonly used to model relationships between pairs of entities. Hyp...
Let A = (a1, a2, ..., an) be a degree sequence of a simple bipartite graph. We present an algorithm ...
In this paper we consider a simple Markov chain for bipartite graphs with given degree sequence on n...
The approximate uniform sampling of graphs with a given degree sequence is a well-known, extensively...
Abstract. The interactions between the components of complex networks are often directed. Proper mod...
Uniform sampling from graphical realizations of a given degree sequence is a fundamental component i...
The switch Markov chain has been extensively studied as the most natural Markov chain Monte Carlo ap...
We consider the well-studied problem of uniformly sampling (bipartite) graphs with a given degree se...
A graph consists of vertices and edges, connecting pairs of vertices. The subject of graph generatio...
Uniform sampling from graphical realizations of a given degree sequence is a fundamental component i...
Many applications require randomly sampling bipartite graphs with fixed degrees, or randomly samplin...
AbstractAn algorithm is presented which randomly selects a labelled graph with specified vertex degr...
Many real-world networks exhibit correlations between the node degrees. For instance, in social netw...
There is a well-known connection between hypergraphs and bipartite graphs, obtained by treating the ...
There is a well-known connection between hypergraphs and bipartite graphs, obtained by treating the ...
Graphs are combinatorial objects commonly used to model relationships between pairs of entities. Hyp...
Let A = (a1, a2, ..., an) be a degree sequence of a simple bipartite graph. We present an algorithm ...
In this paper we consider a simple Markov chain for bipartite graphs with given degree sequence on n...
The approximate uniform sampling of graphs with a given degree sequence is a well-known, extensively...
Abstract. The interactions between the components of complex networks are often directed. Proper mod...
Uniform sampling from graphical realizations of a given degree sequence is a fundamental component i...
The switch Markov chain has been extensively studied as the most natural Markov chain Monte Carlo ap...
We consider the well-studied problem of uniformly sampling (bipartite) graphs with a given degree se...
A graph consists of vertices and edges, connecting pairs of vertices. The subject of graph generatio...
Uniform sampling from graphical realizations of a given degree sequence is a fundamental component i...
Many applications require randomly sampling bipartite graphs with fixed degrees, or randomly samplin...
AbstractAn algorithm is presented which randomly selects a labelled graph with specified vertex degr...
Many real-world networks exhibit correlations between the node degrees. For instance, in social netw...