Pages that link to "Item:Q5412289"
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The following pages link to BIAS MINIMIZATION IN GAUSSIAN PROCESS SURROGATE MODELING FOR UNCERTAINTY QUANTIFICATION (Q5412289):
Displaying 7 items.
- Multi-output local Gaussian process regression: applications to uncertainty quantification (Q385889) (← links)
- Multiscale modeling of failure in composites under model parameter uncertainty (Q498537) (← links)
- A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification (Q727018) (← links)
- Reduced order models for many-query subsurface flow applications (Q1693620) (← links)
- Calibration experimental design considering field response and model uncertainty (Q2309083) (← links)
- A functional data analysis approach to surrogate modeling in reservoir and geomechanics uncertainty quantification (Q2399815) (← links)
- Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark (Q6074252) (← links)
