Results 21 to 30 of about 39,180 (271)
Phase transition in random intersection graphs with communities [PDF]
, 2021 The “random intersection graph with communities” (RIGC) models networks with communities, assuming an underlying bipartite structure of groups and individuals.
van der Hofstad, Remco; id_orcid +10 more
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Mean Hitting Time for Random Walks on a Class of Sparse Networks
Entropy, 2021 For random walks on a complex network, the configuration of a network that provides optimal or suboptimal navigation efficiency is meaningful research. It has been proven that a complete graph has the exact minimal mean hitting time, which grows linearly
Jing Su, Xiaomin Wang, Bing Yao
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Configuration Models as an Urn Problem: The Generalized Hypergeometric Ensemble of Random Graphs [PDF]
, 2021 Abstract A fundamental issue of network data science is the ability to discern observed features that can be expected at random from those beyond such expectations. Configuration models play a crucial role there, allowing us to compare observations against degree-corrected null-models. Nonetheless, existing formulations have limited large-scale
Giona Casiraghi, Vahan Nanumyan
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On limit distributions of vertex degrees in a configuration graph
Transactions of the Karelian Research Centre of the Russian Academy of Sciences, 2015 The configuration graph where vertex degrees are independent identically distributed random variables is often used for models of complex networks such as the Internet. We consider a random graph consisting of N+1 vertices.
Irina Cheplyukova
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ON THE MAXIMUM OF THE MODULARITY OF RANDOM CONFIGURATION GRAPHS
Transactions of the Karelian Research Centre of the Russian Academy of Sciences, 2019 Configuration graphs with random independent identically distributed vertex degrees are considered. The degrees are equal to the number of vertex semiedges that are numbered in an arbitrary order.
Yury Pavlov
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On clustering of conditional configuration graphs
Transactions of the Karelian Research Centre of the Russian Academy of Sciences, 2018 We consider configuration graphs with N vertices. The degrees of the vertices are independent identically distributed limited random variables. They are equal to the number of vertex semiedges that are numbered in an arbitrary order.
Yury Pavlov
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Limit distributions of the number of vertices with given degree in a conditional configuration graph
Transactions of the Karelian Research Centre of the Russian Academy of Sciences, 2016 We consider configuration graphs with N vertices. The degrees of the vertices are independent identically distributed random variables according to power-law distribution. Node degrees form semiedges that are numbered in an arbitrary order.
Yury Pavlov
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Transactions of the Karelian Research Centre of the Russian Academy of Sciences, 2018 We consider configuration graphs with N vertices. The degrees of the vertices are independent random variables identically distributed according to the power law, with a positive parameter τ .
Yury Pavlov
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Random multilinear maps and the Erdős box problem
Discrete Analysis, 2021 Random multilinear maps and the Erdős box problem, Discrete Analysis 2021:17, 8 pp. A major theme in extremal combinatorics is determining the maximum number of edges that a graph or hypergraph can have if it does not contain a certain fixed graph or ...
David Conlon +2 more
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Limit distributions of vertex degrees in a conditional configuration graph
Transactions of the Karelian Research Centre of the Russian Academy of Sciences, 2018 The configuration graph where vertex degrees are independent identically distributed random variables is often used for modeling of complex networks such as the Internet. We consider a random graph consisting of N vertices.
Irina Chepliukova, Yuri Pavlov
doaj +1 more source