activity
19972023
most citedUncovering the overlapping community structure of complex networks in nature and society

5.5k citations · 10.3k across the 59 of their papers we have counts for

collaborators

61 papers

physics.soc-ph2023★ 5 cited

Greedy routing optimisation in hyperbolic networks

Bendegúz Sulyok, Gergely Palla

Finding the optimal embedding of networks into low-dimensional hyperbolic spaces is a challenge that received considerable interest in recent years, with several different approach…

physics.soc-ph2022★ 16 cited

Model-independent methods for embedding directed networks into Euclidean and hyperbolic spaces

Bianka Kovács, Gergely Palla

The arrangement of network nodes in hyperbolic spaces has become a widely studied problem, motivated by numerous results suggesting the existence of hidden metric spaces behind the…

physics.soc-ph2022★ 10 cited

Maximally modular structure of growing hyperbolic networks

Sámuel G. Balogh, Bianka Kovács, Gergely Palla

Hyperbolic models are remarkably good at reproducing the scale-free, highly clustered and small-world properties of networks representing real complex systems in a very simple fram…

physics.soc-ph2021★ 13 cited

Growing hyperbolic networks beyond two dimensions: the generalised popularity-similarity optimisation model

Bianka Kovács, Sámuel G. Balogh, Gergely Palla

Hyperbolic network models have gained considerable attention in recent years, mainly due to their capability of explaining many peculiar features of real-world networks. One of the…

physics.soc-ph2021★ 28 cited

The inherent community structure of hyperbolic networks

Bianka Kovács, Gergely Palla

A remarkable approach for grasping the relevant statistical features of real networks with the help of random graphs is offered by hyperbolic models, centred around the idea of pla…

cs.SI2020★ 12 cited

Optimisation of the coalescent hyperbolic embedding of complex networks

Bianka Kovács, Gergely Palla

Several observations indicate the existence of a latent hyperbolic space behind real networks that makes their structure very intuitive in the sense that the probability for a conn…