As the term “digital twin” spreads across science and technology, it risks losing scientific meaning. Such a twin should not denote just a digital replica, but a computational …
Core-collapse supernovae (CC-SNe) represent the final evolutionary explosive phase of sufficiently massive stars. Their characterization consists in understanding the progenitor …
Reconstructing functional brain networks from functional Magnetic Resonance Imaging (fMRI) data typically relies on statistical pruning, where pairwise correlations between brain …
The dismantling of complex networks due to targeted attacks has been extensively studied in network science 1 . A method to assess the centrality of nodes to prioritize the targets …
Graph generation is a crucial task in many fields, including network science and bioinformatics, as it enables the creation of synthetic graphs that mimic the properties of …
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 …
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 …
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 …
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 …
The study of the behaviors of large community of researchers and what correlations exist between their environment, such as grouping rules by law or specific institution policies, …