Efficient Bayesian inference of subsurface flow models using nested sampling and sparse polynomial chaos surrogates

By Ahmed H. Elsheikh, Ibrahim Hoteit, Mary F. Wheeler. 2014

96 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/eb743593ba8a25d8ed18e3427915531181ea2108

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. M. Christie
2. Ahmed H. Elsheikh
3. Mohammad Hossein Ahmadi
4. Hamid Bazargan

In Statistics and Probability

1. M. Christie
2. Ahmed H. Elsheikh
3. Mohammad Hossein Ahmadi
4. Hamid Bazargan

Citations in the corpus

• Surrogate accelerated sampling of reservoir models with complex structures using sparse polynomial chaos expansion (2015, methodology): “Sparse promoting regularization can be iteratively solved using the orthogonal matching pursuit (OMP) [74, 75] as used in [55] or using the least angle regression (LARS) algorithm [70] as used in [71].”