Zobrazeno 1 - 10
of 148
pro vyhledávání: '"De Bacco, Caterina"'
Autor:
Contisciani, Martina, Hobbhahn, Marius, Power, Eleanor A., Hennig, Philipp, De Bacco, Caterina
Networked datasets are often enriched by different types of information about individual nodes or edges. However, most existing methods for analyzing such datasets struggle to handle the complexity of heterogeneous data, often requiring substantial m
Externí odkaz:
http://arxiv.org/abs/2405.20918
Bicycle infrastructure networks must meet the needs of cyclists to position cycling as a viable transportation choice in cities. In particular, protected infrastructure should be planned cohesively for the whole city and spacious enough to accommodat
Externí odkaz:
http://arxiv.org/abs/2405.02052
Autor:
Safdari, Hadiseh, De Bacco, Caterina
Anomaly detection is an essential task in the analysis of dynamic networks, as it can provide early warning of potential threats or abnormal behavior. We present a principled approach to detect anomalies in dynamic networks that integrates community
Externí odkaz:
http://arxiv.org/abs/2404.10468
Publikováno v:
J. Stat. Mech. (2024) 043403
Hypergraphs are widely adopted tools to examine systems with higher-order interactions. Despite recent advancements in methods for community detection in these systems, we still lack a theoretical analysis of their detectability limits. Here, we deri
Externí odkaz:
http://arxiv.org/abs/2312.00708
Publikováno v:
Nat Commun 15, 7073 (2024)
Many networked datasets with units interacting in groups of two or more, encoded with hypergraphs, are accompanied by extra information about nodes, such as the role of an individual in a workplace. Here we show how these node attributes can be used
Externí odkaz:
http://arxiv.org/abs/2311.03857
Publikováno v:
Phys. Rev. Lett. 133, 057401, 2024
Finding optimal trajectories for multiple traffic demands in a congested network is a challenging task. Optimal transport theory is a principled approach that has been used successfully to study various transportation problems. Its usage is limited b
Externí odkaz:
http://arxiv.org/abs/2309.04727
Autor:
Della Vecchia, Andrea, Neocosmos, Kibidi, Larremore, Daniel B., Moore, Cristopher, De Bacco, Caterina
Publikováno v:
Phys. Rev. E 110, 034310, 2024
We present a physics-inspired method for inferring dynamic rankings in directed temporal networks - networks in which each directed and timestamped edge reflects the outcome and timing of a pairwise interaction. The inferred ranking of each node is r
Externí odkaz:
http://arxiv.org/abs/2307.13544
Global infrastructure robustness and local transport efficiency are critical requirements for transportation networks. However, since passengers often travel greedily to maximize their own benefit and trigger traffic jams, overall transportation perf
Externí odkaz:
http://arxiv.org/abs/2306.16246
Autor:
Lotito, Quintino Francesco, Contisciani, Martina, De Bacco, Caterina, Di Gaetano, Leonardo, Gallo, Luca, Montresor, Alberto, Musciotto, Federico, Ruggeri, Nicolò, Battiston, Federico
Publikováno v:
Journal of Complex Networks, Volume 11, Issue 3, June 2023
From social to biological systems, many real-world systems are characterized by higher-order, non-dyadic interactions. Such systems are conveniently described by hypergraphs, where hyperedges encode interactions among an arbitrary number of units. He
Externí odkaz:
http://arxiv.org/abs/2303.15356
Publikováno v:
Phys. Rev. Research 5, 033084, 2023
Anomaly detection algorithms are a valuable tool in network science for identifying unusual patterns in a network. These algorithms have numerous practical applications, including detecting fraud, identifying network security threats, and uncovering
Externí odkaz:
http://arxiv.org/abs/2302.00504