Sparsifying priors for Bayesian uncertainty quantification in model discovery
We propose a probabilistic model discovery method for identifying ordinary differential equations governing the dynamics of observed multivariate data. Our method is based on the sparse identification of nonlinear dynamics (SINDy) framework, where models are expressed as sparse linear combinations o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
The Royal Society
2022-02-01
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| Series: | Royal Society Open Science |
| Subjects: | |
| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.211823 |