Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Stephanie Nargang"'
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Abstract Based on data from the European banking stress tests of 2014, 2016 and the transparency exercise of 2018 we construct networks of European banks and demonstrate that the latent geometry of these financial networks can be well-represented by
Externí odkaz:
https://doaj.org/article/5d296847ad2447c69558f4e3dcd97927
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Scientific Reports
Scientific Reports
Based on data from the European banking stress tests of 2014, 2016 and the transparency exercise of 2018 we demonstrate for the first time that the latent geometry of financial networks can be well-represented by geometry of negative curvature, i.e.,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7645713bd72348a3f2c59b33ec1fe56e
https://doaj.org/article/5d296847ad2447c69558f4e3dcd97927
https://doaj.org/article/5d296847ad2447c69558f4e3dcd97927
We introduce L-hydra (landmarked hyperbolic distance recovery and approximation), a method for embedding network- or distance-based data into hyperbolic space, which requires only the distance measurements to a few ‘landmark nodes’. This landmark
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10fb208812a7c1e53f8afcf4c68fafe4
http://arxiv.org/abs/2207.06775
http://arxiv.org/abs/2207.06775
We introduce hydra (hyperbolic distance recovery and approximation), a new method for embedding network- or distance-based data into hyperbolic space. We show mathematically that hydra satisfies a certain optimality guarantee: it minimizes the ‘hyp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecb1ff4c55d753886ca9a01bcda3f16a