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All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting
Timely, high-resolution forecasts of infectious disease incidence are useful for policy makers in deciding intervention measures and estimating healthcare resource burden. In this paper, we consider the task of forecasting COVID-19 confirmed cases at the county level for the United States. Although...
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| Publicat a: | medRxiv |
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| Autors principals: | , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Cold Spring Harbor Laboratory
2021
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7987052/ https://ncbi.nlm.nih.gov/pubmed/33758893 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1101/2021.03.12.21253495 |
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