Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Tommaso Rigon"'
Publikováno v:
Methods in Ecology and Evolution, Vol 14, Iss 2, Pp 529-542 (2023)
Abstract Predicting the taxonomic affiliation of DNA sequences collected from biological samples is a fundamental step in biodiversity assessment. This task is performed by leveraging existing databases containing reference DNA sequences endowed with
Externí odkaz:
https://doaj.org/article/6add4acc69fc4caf9d88dfa57f77b97c
Autor:
Carlo Reverberi, Tommaso Rigon, Aldo Solari, Cesare Hassan, Paolo Cherubini, GI Genius CADx Study Group, Andrea Cherubini
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract Artificial Intelligence (ai) systems are precious support for decision-making, with many applications also in the medical domain. The interaction between mds and ai enjoys a renewed interest following the increased possibilities of deep lear
Externí odkaz:
https://doaj.org/article/19f77efcf5f14a58b644e0ef75cb0cc0
Publikováno v:
Journal of the American Statistical Association. :1-13
Publikováno v:
Methods in Ecology and Evolution. 14:529-542
Autor:
Carlo Reverberi, Tommaso Rigon, Aldo Solari, Cesare Hassan, Paolo Cherubini, Andrea Cherubini
Artificial Intelligence (AI) systems are precious support for decision-making, with many applications in the medical domain. However, there is little understanding of how human experts interact with AI. Health policy-makers fear flat reliance on AI a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af673db2d466390bca53528017cd9a25
https://doi.org/10.21203/rs.3.rs-1439843/v1
https://doi.org/10.21203/rs.3.rs-1439843/v1
Autor:
Tommaso Rigon, Emanuele Aliverti
Logistic regression models for binomial responses are routinely used in statistical practice. However, the maximum likelihood estimate may not exist due to data separability. We address this issue by considering a conjugate prior penalty which always
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d46b22b15419488e9608ecefd5b9780
http://arxiv.org/abs/2202.08734
http://arxiv.org/abs/2202.08734
Publikováno v:
Statistics and Computing. 30:1591-1607
Hierarchical normalized discrete random measures identify a general class of priors that is suited to flexibly learn how the distribution of a response variable changes across groups of observations. A special case widely used in practice is the hier
Publikováno v:
Biometrika. 107:891-906
Summary Discrete nonparametric priors play a central role in a variety of Bayesian procedures, most notably when used to model latent features, such as in clustering, mixtures and curve fitting. They are effective and well-developed tools, though the
We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sample. These sequential discoveries are often summarised via accumulation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f790f8778712a1ab2821b80a69bb402b
http://urn.fi/URN:NBN:fi:jyu-202211285379
http://urn.fi/URN:NBN:fi:jyu-202211285379
Autor:
Daniele Durante, Tommaso Rigon
There is a growing interest in learning how the distribution of a response variable changes with a set of observed predictors. Bayesian nonparametric dependent mixture models provide a flexible approach to address this goal. However, several formulat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7ee230bc70bbe41f495c934b001fb8f
http://hdl.handle.net/11565/4041963
http://hdl.handle.net/11565/4041963