activity
20162020
most citedMachine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space

193 citations · 487 across the 12 of their papers we have counts for

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Showing 2017Show all

4 papers · 1 filter

physics.soc-ph2017★ 96 cited

A nonuniform popularity-similarity optimization (nPSO) model to efficiently generate realistic complex networks with communities

Alessandro Muscoloni, Carlo Vittorio Cannistraci

The hidden metric space behind complex network topologies is a fervid topic in current network science and the hyperbolic space is one of the most studied, because it seems associa…

physics.soc-ph2017★ 14 cited

Local-ring network automata and the impact of hyperbolic geometry in complex network link-prediction

Alessandro Muscoloni, Umberto Michieli, Carlo Vittorio Cannistraci

Topological link-prediction can exploit the entire network topology (global methods) or only the neighbourhood (local methods) of the link to predict. Global methods are believed t…

q-bio.NC2017★ 23 cited

Coalescent embedding in the hyperbolic space unsupervisedly discloses the hidden geometry of the brain

Alberto Cacciola, Alessandro Muscoloni, Vaibhav Narula +9

The human brain displays a complex network topology, whose structural organization is widely studied using diffusion tensor imaging. The original geometry from which emerges the ne…

physics.soc-ph2017★ 5 cited

Rich-clubness test: how to determine whether a complex network has or doesn't have a rich-club?

Alessandro Muscoloni, Carlo Vittorio Cannistraci

The rich-club concept has been introduced in order to characterize the presence of a cohort of nodes with a large number of links (rich nodes) that tend to be well connected betwee…