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Learning on dynamic statistical manifolds
Hyperbolic balance laws with uncertain (random) parameters and inputs are ubiquitous in science and engineering. Quantification of uncertainty in predictions derived from such laws, and reduction of predictive uncertainty via data assimilation, remain an open challenge. That is due to nonlinearity o...
Enregistré dans:
| Publié dans: | Proc Math Phys Eng Sci |
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| Auteurs principaux: | , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
The Royal Society Publishing
2020
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7426049/ https://ncbi.nlm.nih.gov/pubmed/32831613 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1098/rspa.2020.0213 |
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