Bayesian model calibration

Closely related to AutoML, in that surrogate optimisation is a popular tool for such, and adaptive design of experiment.

Surrogate optimisation

Classic GP surrogate optimisation is a popular tool for model calibration, see Kennedy and O’Hagan (2001) for a classic example. More recent: Plumlee (2017).


See Dellaporta et al. (2022) for the application of maximum mean discrepancy to the problem of model calibration.


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