19 citations · 43 across the 7 of their papers we have counts for
7 papers
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…
Design Principles for Reproducible Networks
Jasper van der Kolk, Cory Glover, Albert-Lásló Barabási
From protein complexes to electronic circuits, many natural and engineered systems function only if assembled in an exact, reproducible fashion. The structure of each of these syst…
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…
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…
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…
Emergence of geometric Turing patterns in complex networks
Jasper van der Kolk, Guillermo García-Pérez, Nikos E. Kouvaris +2
Turing patterns, arising from the interplay between competing species of diffusive particles, has long been an important concept for describing non-equilibrium self-organization in…
A geometry-induced topological phase transition in random graphs
Jasper van der Kolk, M. Ángeles Serrano, Marián Boguñá
Clustering $\unicode{x2013}$ the tendency for neighbors of nodes to be connected $\unicode{x2013}$ quantifies the coupling of a complex network to its latent metric space. In rando…