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Inference of dynamic systems from noisy and sparse data via manifold-constrained Gaussian processes
Parameter estimation for nonlinear dynamic system models, represented by ordinary differential equations (ODEs), using noisy and sparse data, is a vital task in many fields. We propose a fast and accurate method, manifold-constrained Gaussian process inference (MAGI), for this task. MAGI uses a Gaus...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
National Academy of Sciences
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053978/ https://www.ncbi.nlm.nih.gov/pubmed/33837150 http://dx.doi.org/10.1073/pnas.2020397118 |