MCMC-guided active learning for Gaussian process surrogates outperforms a priori training for Bayesian calibration, and the forward model is the limiting factor, not the MCMC algorithm.
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Integration of Active Learning and MCMC Sampling for Efficient Bayesian Calibration of Mechanical Properties
MCMC-guided active learning for Gaussian process surrogates outperforms a priori training for Bayesian calibration, and the forward model is the limiting factor, not the MCMC algorithm.