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05/05/2023
Robust A-Optimal Experimental Design for Bayesian Inverse Problems
Optimal design of experiments for Bayesian inverse problems has recently...
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01/19/2023
PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments
This paper describes the first version (v1.0) of PyOED, a highly extensi...
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01/15/2021
Stochastic Learning Approach to Binary Optimization for Optimal Design of Experiments
We present a novel stochastic approach to binary optimization for optima...
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07/28/2020
Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations
Optimal experimental design (OED) is the general formalism of sensor pla...
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06/27/2018
An Optimal Experimental Design Framework for Adaptive Inflation and Covariance Localization for Ensemble Filters
Covariance inflation and localization are ubiquitously employed to count...
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02/19/2018
Goal-Oriented Optimal Design of Experiments for Large-Scale Bayesian Linear Inverse Problems
We develop a framework for goal oriented optimal design of experiments (...
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01/02/2018
A Machine Learning Approach to Adaptive Covariance Localization
Data assimilation plays a key role in large-scale atmospheric weather fo...
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04/19/2017
DATeS: A Highly-Extensible Data Assimilation Testing Suite v1.0
A flexible and highly-extensible data assimilation testing suite, named ...
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04/19/2017