Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments
Author:
Funder
U.S. Department of Energy
Publisher
Society for Industrial & Applied Mathematics (SIAM)
Subject
Applied Mathematics,Computational Mathematics
Reference41 articles.
1. On Bayesian A- and D-Optimal Experimental Designs in Infinite Dimensions
2. A-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems with Regularized $\ell_0$-Sparsification
3. A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems
4. Optimal Design of Large-scale Bayesian Linear Inverse Problems Under Reducible Model Uncertainty: Good to Know What You Don't Know
5. Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems
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