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[ascl:2312.003] BUQO: Bayesian Uncertainty Quantification by Optimization

BUQO solves large-scale imaging inverse problems. It leverages probability concentration phenomena and the underlying convex geometry to formulate the Bayesian hypothesis test as a convex problem that is then efficiently solved by using scalable optimization algorithms. This allows scaling to high-resolution and high-sensitivity imaging problems that are computationally unaffordable for other Bayesian computation approaches.

Code site:
https://github.com/basp-group/BUQO
Used in:
https://ui.adsabs.harvard.edu/abs/2021A%26A...649A..99S
Described in:
https://ui.adsabs.harvard.edu/abs/2018arXiv180300889R
Bibcode:
2023ascl.soft12003R

Views: 400

ascl:2312.003
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