A Stochastic Collocation Algorithm with Multifidelity Models

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Survey of multifidelity methods in uncertainty propagation, inference, and optimization (2018, methodology): “A multifidelity method that combines outputs from computationally cheap low-fidelity models with outputs from the high-fidelity model can lead to significant reductions in runtime and provide unbiased estimators of the statistics of the high-fidelity model outputs [76, 150, 148, 198, 160].”
Computational Aspects of Stochastic Collocation with Multifidelity Models (2014, methodology): “Error estimation of this procedure, along with a more rigorous exposition of the method, can be found in [16].”
Review of multi-fidelity models (2016, methodology): “Papers that use deterministic methods for constructing multi-fidelity surrogate models.”