Accelerating Uncertainty Quantification of Groundwater Flow Modelling
Using a Deep Neural Network Proxy

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Accelerating Uncertainty Quantification of Groundwater Flow Modelling Using a Deep Neural Network Proxy

1 July 2020

Mikkel B. Lykkegaard

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Papers citing "Accelerating Uncertainty Quantification of Groundwater Flow Modelling Using a Deep Neural Network Proxy"

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Title
A posteriori stochastic correction of reduced models in delayed acceptance MCMC, with application to multiphase subsurface inverse problems Tiangang Cui C. Fox M. O'Sullivan 37 4 0 10 Sep 2018
Survey of multifidelity methods in uncertainty propagation, inference, and optimization Benjamin Peherstorfer Karen E. Willcox M. Gunzburger AI4CE 48 755 0 28 Jun 2018
Theano: A Python framework for fast computation of mathematical expressions The Theano Development Team Rami Al-Rfou Guillaume Alain Amjad Almahairi Christof Angermüller ... Kelvin Xu Lijun Xue Li Yao Saizheng Zhang Ying Zhang 201 2,340 0 09 May 2016
MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster S. Cotter Gareth O. Roberts Andrew M. Stuart D. White 99 480 0 03 Feb 2012