What is it about?
We develop a cheap approximation of the Bayesian Update. In contrast to the classical Bayesian Update we update not the probability densities, but PCE coefficients, approximated via polynomial chaos expansion.
Photo by Markus Spiske on Unsplash
Why is it important?
Very important for fast and efficient data assimilation. The developed method allows us to incorporate available measurements into existing model.
Read the Original
This page is a summary of: Sampling-free linear Bayesian update of polynomial chaos representations, Journal of Computational Physics, July 2012, Elsevier, DOI: 10.1016/j.jcp.2012.04.044.
You can read the full text:
The following have contributed to this page