Two hybrid Bayesian surrogate training approaches integrate simulation and real-world data via a weighting strategy independent of surrogate family, shown in synthetic and real case studies to improve accuracy and diagnose simulation issues.
Surrogate-based Bayesian comparison of computationally expensive models: Application to microbially induced calcite precipitation
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Bayesian Surrogate Training on Multiple Data Sources: A Hybrid Modeling Strategy
Two hybrid Bayesian surrogate training approaches integrate simulation and real-world data via a weighting strategy independent of surrogate family, shown in synthetic and real case studies to improve accuracy and diagnose simulation issues.