Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments.
<p>Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments.</p>
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2024
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| _version_ | 1852025877128282112 |
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| author | Thomas Gaskin (19865021) |
| author2 | Tim Conrad (3822475) Grigorios A. Pavliotis (7160930) Christof Schütte (151327) |
| author2_role | author author author |
| author_facet | Thomas Gaskin (19865021) Tim Conrad (3822475) Grigorios A. Pavliotis (7160930) Christof Schütte (151327) |
| author_role | author |
| dc.creator.none.fl_str_mv | Thomas Gaskin (19865021) Tim Conrad (3822475) Grigorios A. Pavliotis (7160930) Christof Schütte (151327) |
| dc.date.none.fl_str_mv | 2024-10-17T17:31:45Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0306704.g006 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Results_on_a_reduced_training_dataset_consisting_only_of_the_symptomatic_hospitalized_and_critical_compartments_/27250790 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Medicine Biotechnology Cancer Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified mcmc takes hours making requires knowledge intensive care units chain monte carlo learning probability densities simplified sir model powerful computational method method &# 8217 neural parameter calibration learning infection parameters providing uncertainty quantification learning capabilities uncertainty quantification neural network infection figures contagion parameters accurate calibration ode model complex model xlink "> true posterior small number show convergence sharp focus reduced dataset ready hospitals pandemic projections hospitalisation rates effective policy also demonstrate |
| dc.title.none.fl_str_mv | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_e732e522efbf4c5063fe898ec7c7e2cd |
| identifier_str_mv | 10.1371/journal.pone.0306704.g006 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/27250790 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments.Thomas Gaskin (19865021)Tim Conrad (3822475)Grigorios A. Pavliotis (7160930)Christof Schütte (151327)MedicineBiotechnologyCancerInfectious DiseasesBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedmcmc takes hoursmaking requires knowledgeintensive care unitschain monte carlolearning probability densitiessimplified sir modelpowerful computational methodmethod &# 8217neural parameter calibrationlearning infection parametersproviding uncertainty quantificationlearning capabilitiesuncertainty quantificationneural networkinfection figurescontagion parametersaccurate calibrationode modelcomplex modelxlink ">true posteriorsmall numbershow convergencesharp focusreduced datasetready hospitalspandemic projectionshospitalisation rateseffective policyalso demonstrate<p>Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments.</p>2024-10-17T17:31:45ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0306704.g006https://figshare.com/articles/figure/Results_on_a_reduced_training_dataset_consisting_only_of_the_symptomatic_hospitalized_and_critical_compartments_/27250790CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/272507902024-10-17T17:31:45Z |
| spellingShingle | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments. Thomas Gaskin (19865021) Medicine Biotechnology Cancer Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified mcmc takes hours making requires knowledge intensive care units chain monte carlo learning probability densities simplified sir model powerful computational method method &# 8217 neural parameter calibration learning infection parameters providing uncertainty quantification learning capabilities uncertainty quantification neural network infection figures contagion parameters accurate calibration ode model complex model xlink "> true posterior small number show convergence sharp focus reduced dataset ready hospitals pandemic projections hospitalisation rates effective policy also demonstrate |
| status_str | publishedVersion |
| title | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments. |
| title_full | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments. |
| title_fullStr | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments. |
| title_full_unstemmed | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments. |
| title_short | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments. |
| title_sort | Results on a reduced training dataset, consisting only of the symptomatic, hospitalized, and critical compartments. |
| topic | Medicine Biotechnology Cancer Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified mcmc takes hours making requires knowledge intensive care units chain monte carlo learning probability densities simplified sir model powerful computational method method &# 8217 neural parameter calibration learning infection parameters providing uncertainty quantification learning capabilities uncertainty quantification neural network infection figures contagion parameters accurate calibration ode model complex model xlink "> true posterior small number show convergence sharp focus reduced dataset ready hospitals pandemic projections hospitalisation rates effective policy also demonstrate |