collaborators

12 papers

physics.soc-ph2026

Heuristic and exact modularity optimization with size-constrained communities

Filipi N. Silva, Samin Aref, Vincent Traag +1

When searching for communities in networks, domain experts may have some prior expectations about the size of communities. Yet, community detection methods normally do not optimize…

cs.LG2026

Task complexity shapes internal representations and robustness in neural networks

Robert Jankowski, Filippo Radicchi, M. Ángeles 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…

physics.soc-ph2026

Multilayer network science: theory, methods, and applications

Alberto Aleta, Andreia Sofia Teixeira, Guilherme Ferraz de Arruda +14

Multilayer network science has emerged as a central framework for analysing interconnected and interdependent complex systems. Its relevance has grown substantially with the increa…

cs.LG2026

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…

physics.soc-ph2026

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…

physics.soc-ph2026

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…