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Bayesian uncertainty quantification for data-driven equation learning
Equation learning aims to infer differential equation models from data. While a number of studies have shown that differential equation models can be successfully identified when the data are sufficiently detailed and corrupted with relatively small amounts of noise, the relationship between observa...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548080/ https://www.ncbi.nlm.nih.gov/pubmed/35153587 http://dx.doi.org/10.1098/rspa.2021.0426 |