94 citations · 94 across the 5 of their papers we have counts for
5 papers
Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN Performance
Roya Aliakbarisani, Robert Jankowski, M. Ángeles Serrano +1
Graph Neural Networks (GNNs) have excelled in predicting graph properties in various applications ranging from identifying trends in social networks to drug discovery and malware d…
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…
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…
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…
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…