13 papers
Efficient generation of networks with minimal average shortest-path distance
Meritxell Vila-Miñana, Filippo Radicchi
Designing networks that minimize distances and satisfy structural constraints is a fundamental task across transportation, communication, and biological systems. Here, we consider…
Task complexity shapes internal representations and robustness in neural networks
Robert Jankowski, Filippo Radicchi, M. Ãngeles Serrano +2
Neural networks excel across a wide range of tasks, yet remain black boxes. In particular, how their internal representations are shaped by the complexity of the input data and the…
Dynamical processes and emergent behaviors in multiplex networks
Federico Battiston, Mattia Frasca, Jesus Gómez-Gardeñes +4
Over the last two decades, network science has greatly advanced our understanding of how the collective behaviors of a complex system emerge from the interactions among its basic u…
Robustness in sparse artificial neural networks trained with adaptive topology
Bendegúz Sulyok, Gergely Palla, Filippo Radicchi +1
We investigate the robustness of sparse artificial neural networks trained with adaptive topology. We focus on a simple yet effective architecture consisting of three sparse layers…
Modeling plant disease spread via high-resolution human mobility networks
Varun K. Rao, Ryan Higgs, Hautahi Kingi +3
Human mobility plays a crucial role in the spread of human diseases, but is rarely quantified in plant disease epidemics. To address this gap, we integrate a unique, high-resolutio…
Modeling individual attention dynamics on online social media
Jaume Ojer, Filippo Radicchi, Santo Fortunato +2
In the attention economy, understanding how individuals manage limited attention is critical. We introduce a simple model describing the decay of a user's engagement when facing mu…