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20192025
most citedPredictability of missing links in complex networks

3 citations · 3 across the 6 of their papers we have counts for

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Showing physics.soc-phShow all

5 papers · 1 filter

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

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-ph2023

Feature-enriched hyperbolic network geometry

Roya Aliakbarisani, M. Ángeles Serrano, Marián Boguñá

Graph-structured data provide a comprehensive description of complex systems, encompassing not only the interactions among nodes but also the intrinsic features that characterize t…

physics.soc-ph2019★ 3 cited

Predictability of missing links in complex networks

Guillermo García-Pérez, Roya Aliakbarisani, Abdorasoul Ghasemi +1

Predicting missing links in real networks is an important problem in network science to which considerable efforts have been devoted, giving as a result a vast plethora of link pre…