scholarly journals Optimal Design of Large-scale Bayesian Linear Inverse Problems Under Reducible Model Uncertainty: Good to Know What You Don't Know

2021 ◽  
Vol 9 (1) ◽  
pp. 163-184
Author(s):  
Alen Alexanderian ◽  
Noemi Petra ◽  
Georg Stadler ◽  
Isaac Sunseri
Keyword(s):  
Optimal Design ◽  
Inverse Problems ◽  
Model Uncertainty ◽  
Large Scale ◽  
Linear Inverse Problems

scholarly journals Randomization and Reweighted $\ell_1$-Minimization for A-Optimal Design of Linear Inverse Problems

2020 ◽  
Vol 42 (3) ◽  
pp. A1714-A1740
Author(s):  
Elizabeth Herman ◽  
Alen Alexanderian ◽  
Arvind K. Saibaba
Keyword(s):  
Optimal Design ◽  
Inverse Problems ◽  
Linear Inverse Problems

Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations

2011 ◽  
Vol 33 (1) ◽  
pp. 407-432 ◽  
Author(s):  
H. P. Flath ◽  
L. C. Wilcox ◽  
V. Akçelik ◽  
J. Hill ◽  
B. van Bloemen Waanders ◽  
...  
Keyword(s):  
Inverse Problems ◽  
Uncertainty Quantification ◽  
Large Scale ◽  
Fast Algorithms ◽  
Low Rank ◽  
Linear Inverse Problems

An object-oriented optimization framework for large-scale inverse problems

2021 ◽  
pp. 104790
Author(s):  
Ettore Biondi ◽  
Guillaume Barnier ◽  
Robert G. Clapp ◽  
Francesco Picetti ◽  
Stuart Farris
Keyword(s):  
Inverse Problems ◽  
Large Scale ◽  
Object Oriented ◽  
Optimization Framework
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