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Variational Kinetic Clustering of Complex Networks
2022
Journal of Chemical Physics
Efficiently identifying the most important communities and key transition nodes in weighted and unweighted networks is a prevalent problem in a wide range of disciplines. Here we focus on the optimal clustering using variational kinetic parameters, linked to Markov processes defined on the underlying networks, namely the slowest relaxation time and the Kemeny constant. We derive novel relations in terms of mean first passage times for optimizing clustering via the Kemeny constant, and show that
doi:10.1063/5.0105099
pmid:36922127
fatcat:lt4mwkinongpvejw6jrncbawbe