Pages that link to "Item:Q1787655"

The following pages link to Machine-learning-based modeling of coarse-scale error, with application to uncertainty quantification (Q1787655):

Displaying 9 items.

• Local and global error models to improve uncertainty quantification (Q500756) (← links)
• A machine learning approach for efficient uncertainty quantification using multiscale methods (Q1700748) (← links)
• The use of flow diagnostics to rank model ensembles (Q2085047) (← links)
• Use of low-fidelity models with machine-learning error correction for well placement optimization (Q2085088) (← links)
• Multiscale uncertainty quantification with arbitrary polynomial chaos (Q2179186) (← links)
• A data-space inversion procedure for well control optimization and closed-loop reservoir management (Q2185952) (← links)
• Multifidelity framework for uncertainty quantification with multiple quantities of interest (Q2185990) (← links)
• Uncertainty quantification in scientific machine learning: methods, metrics, and comparisons (Q2681129) (← links)
• Prediction of permeability of porous media using optimized convolutional neural networks (Q2683510) (← links)