activity
19982025
most citedProbability distributions generated by fractional diffusion equations

158 citations · 403 across the 15 of their papers we have counts for

collaborators

17 papers

physics.flu-dyn2025

Event-based complexity in atmospheric turbulence

Paolo Paradisi, Rita Cesari

Since the studies of Kolmogorov and Oboukhov in 1941, the problem of intermittent large velocity excursions was recognized to be one of the most intriguing and elusive aspects of t…

physics.comp-ph2025

Robustness of complexity estimation in event-driven signals against accuracy of event detection method

Marco Cafiso, Paolo Paradisi

Complexity has gained recent attention in machine learning for its ability to extract synthetic information from large datasets. Complex dynamical systems are characterized by temp…

q-bio.NC2024★ 2 cited

Temporal Complexity of a Hopfield-Type Neural Model in Random and Scale-Free Graphs

Marco Cafiso, Paolo Paradisi

The Hopfield network model and its generalizations were introduced as a model of associative, or content-addressable, memory. They were widely investigated both as an unsupervised…

cond-mat.stat-mech2022★ 20 cited

Anomalous diffusion originated by two Markovian hopping-trap mechanisms

Silvia Vitali, Paolo Paradisi, Gianni Pagnini

We show through intensive simulations that the paradigmatic features of anomalous diffusion are indeed the features of a (continuous-time) random walk driven by two different Marko…

cond-mat.stat-mech2018★ 16 cited

Finite-energy Lévy-type motion through heterogeneous ensemble of Brownian particles

Oleksii Yu. Sliusarenko, Silvia Vitali, Vittoria Sposini +4

Complex systems display anomalous diffusion, whose signature is a space/time scaling with in the Probability Density Function (PDF). Anomalous diffusion can…

cond-mat.stat-mech2018

Langevin equation in complex media and anomalous diffusion

Silvia Vitali, Vittoria Sposini, Oleksii Sliusarenko +3

The problem of biological motion is a very intriguing and topical issue. Many efforts are being focused on the development of novel modeling approaches for the description of anoma…