activity
20032026
most citedBenchmark graphs for testing community detection algorithms

3.1k citations · 12.5k across the 87 of their papers we have counts for

collaborators

88 papers

physics.soc-ph2026

Enabling quantum communication in ultra-large-scale networks

Filippo Radicchi

The recent development of small-scale quantum networks poses the question of whether such a technology could also operate at scale in the futuristic Quantum Internet. The question…

physics.soc-ph2023★ 1 cited

Network community detection via neural embeddings

Sadamori Kojaku, Filippo Radicchi, Yong-Yeol Ahn +1

Recent advances in machine learning research have produced powerful neural graph embedding methods, which learn useful, low-dimensional vector representations of network data. Thes…

physics.soc-ph2023★ 11 cited

Epidemic spreading in group-structured populations

Siddharth Patwardhan, Varun K. Rao, Santo Fortunato +1

Individuals involved in common group activities/settings -- e.g., college students that are enrolled in the same class and/or live in the same dorm -- are exposed to recurrent cont…

physics.soc-ph2023★ 11 cited

Heterogeneous message passing for heterogeneous networks

George T. Cantwell, Alec Kirkley, Filippo Radicchi

Message passing (MP) is a computational technique used to find approximate solutions to a variety of problems defined on networks. MP approximations are generally accurate in local…

physics.soc-ph2023★ 1 cited

Dynamical Methods for Target Control of Biological Networks

Thomas Parmer, Filippo Radicchi

Estimating the influence that individual nodes have on one another in a Boolean network is essential to predict and control the system's dynamical behavior, for example, detecting…

cond-mat.stat-mech2023★ 2 cited

Critical avalanches of Susceptible-Infected-Susceptible dynamics in finite networks

Daniele Notarmuzi, Alessandro Flammini, Claudio Castellano +1

We investigate the avalanche temporal statistics of the Susceptible-Infected-Susceptible (SIS) model when the dynamics is critical and takes place on finite random networks. By con…