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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...
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| Vydáno v: | Proc Natl Acad Sci U S A |
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| Hlavní autoři: | , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
National Academy of Sciences
2021
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8053978/ https://ncbi.nlm.nih.gov/pubmed/33837150 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.2020397118 |
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