Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Giona C"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Positive and negative relations play an essential role in human behavior and shape the communities we live in. Despite their importance, data about signed relations is rare and commonly gathered through surveys. Interaction data is more abun
Externí odkaz:
https://doaj.org/article/11ac3a6d8bfc44c89f26ec6123ebe1e6
Publikováno v:
Applied Network Science, Vol 8, Iss 1, Pp 1-20 (2023)
Abstract Apart from nodes and links, for many networked systems, we have access to data on paths, i.e., collections of temporally ordered variable-length node sequences that are constrained by the system’s topology. Understanding the patterns in su
Externí odkaz:
https://doaj.org/article/3953d41fb2e247478feaf133a2d2811f
Publikováno v:
In The Journal of Urology 2004 172(1):76-80
Autor:
Giona Casiraghi, Vahan Nanumyan
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract A fundamental issue of network data science is the ability to discern observed features that can be expected at random from those beyond such expectations. Configuration models play a crucial role there, allowing us to compare observations a
Externí odkaz:
https://doaj.org/article/884e3af5cceb4c709975bc5897ca787e
Autor:
Giona Casiraghi
Publikováno v:
Applied Network Science, Vol 4, Iss 1, Pp 1-22 (2019)
Abstract We provide a novel family of generative block-models for random graphs that naturally incorporates degree distributions: the block-constrained configuration model. Block-constrained configuration models build on the generalized hypergeometri
Externí odkaz:
https://doaj.org/article/eeac676cb6f74bd88c803b9cee5854fa
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 7 (2021)
The dynamics of collaboration networks of firms follow a life cycle of growth and decline. That does not imply they also become less resilient. Instead, declining collaboration networks may still have the ability to mitigate shocks from firms leaving
Externí odkaz:
https://doaj.org/article/6a5b6a73aa0c41adab9d77f4f72eca3e
Publikováno v:
Frontiers in Physics, Vol 8 (2020)
We investigate a multi-agent model of firms in a Research & Development (R&D) network. Each firm is characterized by its knowledge stock xi(t), which follows a non-linear dynamics. xi(t) grows with the input from other firms, i.e., by knowledge trans
Externí odkaz:
https://doaj.org/article/68ce39d8fd2e4055b5e33cafa45453a8