976 citations · 1.1k across the 4 of their papers we have counts for
4 papers
Unifying equivalences across unsupervised learning, network science, and imaging/network neuroscience
Mika Rubinov
Modern scientific fields face the challenge of integrating a wealth of data, analyses, and results. We recently showed that a neglect of this integration can lead to circular analy…
Scaling Properties of Human Brain Functional Networks
Riccardo Zucca, Xerxes D. Arsiwalla, Hoang Le +2
We investigate scaling properties of human brain functional networks in the resting-state. Analyzing network degree distributions, we statistically test whether their tails scale a…
A Unifying Framework for Measuring Weighted Rich Clubs
Jeff Alstott, Pietro Panzarasa, Mikail Rubinov +2
Network analysis can help uncover meaningful regularities in the organization of complex systems. Among these, rich clubs are a functionally important property of a variety of soci…
Weight-conserving characterization of complex functional brain networks
Mikail Rubinov, Olaf Sporns
Complex functional brain networks are large networks of brain regions and functional brain connections. Statistical characterizations of these networks aim to quantify global and l…