Implements a derivative-free machine-learning-accelerated pipeline for uncertainty quantification.
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- How do I build prior distributions?
- How do I build good observational noise covariances
- What ensemble size should I take? Which process should I use? What is the recommended configuration?
- Where can I walk through the simple example?
- What is the
EnsembleKalmanProcesses.jlpackage? - What are the recommendations/defaults for dimension reduction or data processing?
- How to I plot or interpret the posterior distribution?