Tommaso Gili

Jan 17, 2025 | link.aps.org | Pablo Villegas |Andrea Gabrielli |Anna Poggialini |Tommaso Gili

Heterogeneous and complex networks represent intertwined interactions between real-world elements or agents. Determining the multiscale mesoscopic organization of clusters and intertwined structures is still a fundamental and open problem of complex network theory. By taking advantage of the recent Laplacian renormalization group (LRG), we scrutinize information diffusion pathways throughout networks to shed further light on this issue.

Oct 22, 2024 | biorxiv.org | Gabriele Di Antonio |Tommaso Gili |Andrea Gabrielli |Maurizio Mattia

AbstractExploring the dynamics of a complex system, such as the human brain, poses significant challenges due to inherent uncertainties and limited data. In this study, we enhance the capabilities of noisy linear recurrent neural networks (lRNNs) within the reservoir computing framework, demonstrating their effectiveness in creating autonomous in silico replicas - digital twins - of brain activity.

Apr 19, 2024 | link.aps.org | Pablo Villegas |Universidad de Granada |Tommaso Gili |Guido Caldarelli

Abstract Tropical rainforests exhibit a rich repertoire of spatial patterns emerging from the intricate relationship between the microscopic interaction between species. In particular, the distribution of vegetation clusters can shed much light on the underlying process that regulates the ecosystem.