Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Tuomas Sivula"'
Autor:
Jarno Lintusaari, Paul Blomstedt, Brittany Rose, Tuomas Sivula, Michael U. Gutmann, Samuel Kaski, Jukka Corander
Publikováno v:
Wellcome Open Research, Vol 4 (2019)
Earlier research has suggested that approximate Bayesian computation (ABC) makes it possible to fit simulator-based intractable birth–death models to investigate communicable disease outbreak dynamics with accuracy comparable to that of exact Bayes
Externí odkaz:
https://doaj.org/article/60ae912e26c54448ad8a18c4be90a9cd
Publikováno v:
Communications in Statistics - Theory and Methods. :1-23
When evaluating and comparing models using leave-one-out cross-validation (LOO-CV), the uncertainty of the estimate is typically assessed using the variance of the sampling distribution. Considering the uncertainty is important, as the variability of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e133f2dad2f13c0799060861a503cbfd
https://doi.org/10.1080/03610926.2021.2021240
https://doi.org/10.1080/03610926.2021.2021240
Autor:
Karri Sunila, Henri Karikallio, Simon Holmbacka, Eero Siivola, Ilkka Raiskinen, Jarno Niemela, Juho Piironen, Tuomas Sivula
Publikováno v:
ICT
Antenna line alarms are a significant indicator for failing components in LTE base stations. By predicting such alarms it is possible to prepare for system repairs or for system resets in advance, which reduces the maintenance downtime for LTE operat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a40aa874105232ca4cbb62464a11c5da
https://doi.org/10.1109/ict.2018.8464882
https://doi.org/10.1109/ict.2018.8464882
Publikováno v:
Vehtari, A, Mononen, T, Tolvanen, V, Sivula, T & Winther, O 2016, ' Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models ', Journal of Machine Learning Research, vol. 17, pp. 1-38 .
Scopus-Elsevier
Technical University of Denmark Orbit
Aalto University
Scopus-Elsevier
Technical University of Denmark Orbit
Aalto University
The future predictive performance of a Bayesian model can be estimated using Bayesian cross-validation. In this article, we consider Gaussian latent variable models where the integration over the latent values is approximated using the Laplace method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea8cc0196ba22bf1d3d34716089cbd5b
https://orbit.dtu.dk/en/publications/40b92833-33e4-4423-bc42-1ea55f259546
https://orbit.dtu.dk/en/publications/40b92833-33e4-4423-bc42-1ea55f259546
