From the 1 of 13 linked papers with an AI index.
1 citations · 1 across the 5 of their papers we have counts for
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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…
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…
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…
Mapping bipartite networks into multidimensional hyperbolic spaces
Robert Jankowski, Roya Aliakbarisani, M. Ãngeles 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…
Extracting the geometric backbone of bipartite networks
LucÃa S. RamÃrez, Roya Aliakbarisani, M. Ãngeles 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…
Clustering Does Not Always Imply Latent Geometry
Roya Aliakbarisani, Marián Boguñá, M. Ãngeles 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…