Robustness and resilience of complex networks
Complex networks are ubiquitous: a cell, the human brain, a group of people and the Internet are all examples of interconnected many-body systems characterized by macroscopic …
Geometric deep learning sub-network extraction for maximum clique enumeration
In this paper we propose a method based on geometric deep learning to reduce the computational complexity of the Maximum Clique Enumeration (MCE) problem. Specifically, given a …
Learning fine-grained search space pruning and heuristics for combinatorial optimization
Combinatorial optimization problems arise naturally in a wide range of applications from diverse domains. Many of these problems are NP-hard and designing efficient heuristics for …
Link Prediction in Time Varying Social Networks
Insights into countries’ exposure and vulnerability to food trade shocks from network-based simulations
In the context of a global food system, the dynamics associated to international food trade have become key determinants of food security. In this paper, we resort to a diffusion …
Efficient Node PageRank Improvement via Link Building using Geometric Deep Learning
Centrality is a relevant topic in the field of network research, due to its various theoretical and practical implications. In general, all centrality metrics aim at measuring the …
Correlation between researchers’ centrality and h-index: a case study
(Unintended) Consequences of export restrictions on medical goods during the Covid-19 pandemic
The outbreak of the Covid-19 pandemic led several governments to impose restrictions on the export of medical supplies. Despite being at odds with the canonical prescriptions of …
Machine learning dismantling and early-warning signals of disintegration in complex systems
From physics to engineering, biology and social science, natural and artificial systems are characterized by interconnected topologies whose features – e.g., heterogeneous …


