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20112020
most citedMachine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space

193 citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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4 papers · 1 filter

physics.soc-ph2019★ 35 cited

Navigability evaluation of complex networks by greedy routing efficiency

Alessandro Muscoloni, Carlo Vittorio Cannistraci

Network navigability is a key feature of complex networked systems. For a network embedded in a geometrical space, maximization of greedy routing (GR) measures based on the node ge…

physics.soc-ph2018★ 14 cited

Minimum curvilinear automata with similarity attachment for network embedding and link prediction in the hyperbolic space

Alessandro Muscoloni, Carlo Vittorio Cannistraci

The idea of minimum curvilinearity (MC) is that the hidden geometry of complex networks, in particular when they are sufficiently sparse, clustered, small-world and heterogeneous,…

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…