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Goal-oriented optimal experimental design for Bayesian linear inverse problem

The code runs in the environment of hIPPYlib (https://hippylib.github.io)

Numerical experiment on advection-diffusion model in /hippylib/gooed/adv_predict9.py for 9 candidate sensors /hippylib/gooed/adv_predict75.py for 75 candidate sensors

@Article{WuChenGhattas21, author = {Wu, Keyi and Chen, Peng and Ghattas, Omar}, title = {An efficient method for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placemen}, journal = {arXiv preprint arXiv:2102.06627}, year = {2021}, timestamp = {2021-09-15}, }

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A fast and scalable computational framework for goal-oriented Bayesian optimal experimental design

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