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The HyperKron Graph Model for higher-order features
[article]
2018
arXiv
pre-print
Graph models have long been used in lieu of real data which can be expensive and hard to come by. A common class of models constructs a matrix of probabilities, and samples an adjacency matrix by flipping a weighted coin for each entry. Examples include the Erdős-Rényi model, Chung-Lu model, and the Kronecker model. Here we present the HyperKron Graph model: an extension of the Kronecker Model, but with a distribution over hyperedges. We prove that we can efficiently generate graphs from this
arXiv:1809.03488v1
fatcat:h7j5xu3ydrbaxghptugdekxhtq