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...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Royal Society
2021
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