A spectral clustering method for temporal networks is developed using multi-view CCA and time-reversible random walks on an augmented space-time network to detect evolving communities as metastable structures.
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Connects continuum stochastic signals to graphon random walks via Koopman and Perron-Frobenius operators for spectral clustering and graphon reconstruction from data.
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Spectral clustering of time-evolving networks using spatio-temporal random walks
A spectral clustering method for temporal networks is developed using multi-view CCA and time-reversible random walks on an augmented space-time network to detect evolving communities as metastable structures.