Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Riccardo Rastelli"'
Publikováno v:
IEEE Access, Vol 11, Pp 117971-117983 (2023)
Representing the nodes of continuous-time temporal graphs in a low-dimensional latent space has wide-ranging applications, from prediction to visualization. Yet, analyzing continuous-time relational data with timestamped interactions introduces uniqu
Externí odkaz:
https://doaj.org/article/52105b9fdb8f4b7dab0b81e31ccfe0f9
Publikováno v:
Empirical Economics. 63:345-389
This paper introduces a novel framework to study default dependence and systemic risk in a financial network that evolves over time. We analyse several indicators of risk, and develop a new latent space model to assess the health of key European bank
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36de188e5fd245599aa76fbd79c184c7
https://doi.org/10.1007/s00181-021-02135-y
https://doi.org/10.1007/s00181-021-02135-y
Autor:
Michael Fop, Riccardo Rastelli
Publikováno v:
Advances in Data Analysis and Classification. 14:485-512
We propose a new stochastic block model that focuses on the analysis of interaction lengths in dynamic networks. The model does not rely on a discretization of the time dimension and may be used to analyze networks that evolve continuously over time.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85213c05983871678695b6ce498d9200
https://doi.org/10.1007/s11634-020-00403-w
https://doi.org/10.1007/s11634-020-00403-w
Autor:
Riccardo Rastelli, Hugo Dolan
Publikováno v:
Statistics in Biosciences
We study how international flights can facilitate the spread of an epidemic to a worldwide scale. We combine an infrastructure network of flight connections with a population density dataset to derive the mobility network, and then we define an epide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9c05b3786fd18e7f21e99d35b0b0c63
http://arxiv.org/abs/2009.12964
http://arxiv.org/abs/2009.12964
Publikováno v:
Network Science
Network Science, Cambridge Journals, 2018, 6, pp.469-493
Network Science, Cambridge Journals, 2018, 6, pp.469-493
Latent stochastic block models are flexible statistical models that are widely used in social network analysis. In recent years, efforts have been made to extend these models to temporal dynamic networks, whereby the connections between nodes are obs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdb5c99aae43d6744b9a98b8da5e221e
https://doi.org/10.1017/nws.2018.19
https://doi.org/10.1017/nws.2018.19
Publikováno v:
Proceedings of the National Academy of Sciences. 113:6629-6634
We analyze the temporal bipartite network of the leading Irish companies and their directors from 2003 to 2013, encompassing the end of the Celtic Tiger boom and the ensuing financial crisis in 2008. We focus on the evolution of company interlocks, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42c2a02dde79d73a3c66fd5c6528b475
https://doi.org/10.1073/pnas.1606295113
https://doi.org/10.1073/pnas.1606295113
Publikováno v:
Network Science. 4(04):407-432
We derive properties of Latent Variable Models for networks, a broad class ofmodels that includes the widely-used Latent Position Models. These include theaverage degree distribution, clustering coefficient, average path length and degreecorrelations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64ac2b1e4f71d1345ce2502230b9cb98
https://research.wu.ac.at/de/publications/bd232c35-5758-461e-b51f-d0cb3f9fd0a6
https://research.wu.ac.at/de/publications/bd232c35-5758-461e-b51f-d0cb3f9fd0a6
Autor:
Riccardo Rastelli, Nial Friel
Publikováno v:
Statistics and Computing
In cluster analysis interest lies in probabilistically capturing partitions of individuals, items or observations into groups, such that those belonging to the same group share similar attributes or relational profiles. Bayesian posterior samples for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29f64e3f967d506ae0dd8b338e6ff73d
https://doi.org/10.1007/s11222-017-9786-y
https://doi.org/10.1007/s11222-017-9786-y
The integrated completed likelihood (ICL) criterion has proven to be a very popular approach in model-based clustering through automatically choosing the number of clusters in a mixture model. This approach effectively maximises the complete data lik
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78f0bb787b5ba12960b91b56d4a76482