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20162026
most citedHidden geometric correlations in real multiplex networks

147 citations · 466 across the 22 of their papers we have counts for

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Showing physics.soc-phShow all

15 papers · 1 filter

physics.soc-ph2026

Latent geometry organizes higher-order interactions

Berné L. Nortier, Jasper van der Kolk, Robert Jankowski +4

Higher-order structures offer a natural representation of complex systems that involve interactions between groups of different sizes. A widespread feature of their higher-order st…

physics.soc-ph2025

Extracting the geometric backbone of bipartite networks

Lucía S. Ramírez, Roya Aliakbarisani, M. Ángeles Serrano +1

Real bipartite networks combine degree-constrained random mixing with structured, locality-like rules. We introduce a statistical filter that benchmarks node-level bipartite cluste…

physics.soc-ph2025★ 1 cited

Trade-offs between structural richness and perceptual robustness in music network representations

Lluc Bono Rosselló, Robert Jankowski, Hugues Bersini +2

Music is a structured and perceptually rich sequence of sounds in time, whose perception is shaped by the interplay of expectation and uncertainty about what comes next. Yet the un…

physics.soc-ph2025

Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis

Aina Ferrà Marcús, Robert Jankowski, Meritxell Vila Miñana +2

Many complex networks, ranging from social to biological systems, exhibit structural patterns consistent with an underlying hyperbolic geometry. Revealing the dimensionality of thi…

physics.soc-ph2025

Multiplexity amplifies geometry in networks

Jasper van der Kolk, Dmitri Krioukov, Marián Boguñá +1

Many real-world network are multilayer, with nontrivial correlations across layers. Here we show that these correlations amplify geometry in networks. We focus on mutual clustering…

physics.soc-ph2025

Clustering Does Not Always Imply Latent Geometry

Roya Aliakbarisani, Marián Boguñá, M. Ángeles Serrano

The latent space approach to complex networks has revealed fundamental principles and symmetries, enabling geometric methods. However, the conditions under which network topology i…

physics.soc-ph2025

Mapping bipartite networks into multidimensional hyperbolic spaces

Robert Jankowski, Roya Aliakbarisani, M. Ángeles Serrano +1

Bipartite networks appear in many real-world contexts, linking entities across two distinct sets. They are often analyzed via one-mode projections, but such projections can introdu…

physics.soc-ph2024

Renormalization of networks with weak geometric coupling

Jasper van der Kolk, Marián Boguñá, M. Ángeles Serrano

The Renormalization Group is crucial for understanding systems across scales, including complex networks. Renormalizing networks via network geometry, a framework in which their to…

physics.soc-ph2024

Feature-aware ultra-low dimensional reduction of real networks

Robert Jankowski, Pegah Hozhabrierdi, Marián Boguñá +1

In existing models and embedding methods of networked systems, node features describing their qualities are usually overlooked in favor of focusing solely on node connectivity. Thi…

physics.soc-ph2023★ 7 cited

Random graphs and real networks with weak geometric coupling

J. van der Kolk, M. Á. Serrano, M. Boguñá

Geometry can be used to explain many properties commonly observed in real networks. It is therefore often assumed that real networks, especially those with high average local clust…

physics.soc-ph2023

The D-Mercator method for the multidimensional hyperbolic embedding of real networks

Robert Jankowski, Antoine Allard, Marián Boguñá +1

One of the pillars of the geometric approach to networks has been the development of model-based mapping tools that embed real networks in its latent geometry. In particular, the t…

physics.soc-ph2017★ 38 cited

Soft communities in similarity space

Guillermo García-Pérez, M. Ángeles Serrano, Marián Boguñá

The model has been a central geometric model in the development of the field of network geometry. It has been mainly studied in its homogeneous regime, in which angu…

physics.soc-ph2017★ 61 cited

Geometric correlations mitigate the extreme vulnerability of multiplex networks against targeted attacks

Kaj-Kolja Kleineberg, Lubos Buzna, Fragkiskos Papadopoulos +2

We show that real multiplex networks are unexpectedly robust against targeted attacks on high degree nodes, and that hidden interlayer geometric correlations predict this robustnes…

physics.soc-ph2016★ 147 cited

Hidden geometric correlations in real multiplex networks

Kaj-Kolja Kleineberg, Marian Boguna, M. Angeles Serrano +1

Real networks often form interacting parts of larger and more complex systems. Examples can be found in different domains, ranging from the Internet to structural and functional br…

physics.soc-ph2016★ 94 cited

The hidden geometry of weighted complex networks

Antoine Allard, M. Ángeles Serrano, Guillermo García-Pérez +1

The topology of many real complex networks has been conjectured to be embedded in hidden metric spaces, where distances between nodes encode their likelihood of being connected. Be…