A decomposed multi-fidelity covariance formulation allows Vecchia approximation on latent processes and GLS mean removal to deliver scalable, fully likelihood-based fusion of noisy low-fidelity and accurate high-fidelity spatio-temporal data.
arXiv preprint arXiv:1604.07484 , year=
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A new framework for non-stationary spatio-temporal data fusion of multi-fidelity models
A decomposed multi-fidelity covariance formulation allows Vecchia approximation on latent processes and GLS mean removal to deliver scalable, fully likelihood-based fusion of noisy low-fidelity and accurate high-fidelity spatio-temporal data.