Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion

Ghattas, Omar; Marzouk, Youssef; Parno, Matthew; Petra, Noemi; Villa, Umberto

doi:10.6084/m9.figshare.4602481.v1

poster-muq-hip-nsfssi2-1550593.pdf (5.16 MB)

Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion

journal contribution

posted on 2017-02-18, 16:26 authored by Omar Ghattas, Youssef Marzouk, Matthew Parno, Noemi Petra, Umberto VillaUmberto Villa

2017 NSF SI2 PI meeting
Feb. 21-22, Arlington, VA

NSF SI2-SSI project:
Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion

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NSF Awards ACI-1550487, ACI-1550547, and ACI-1550593

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NSF-SI2-2017 Inverse problems Bayesian Inference Data Science Scientific computing c++python Numerical Analysis Mathematical Software Open Software Applied Statistics Optimisation

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CC BY 4.0

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Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion

Funding

NSF Awards ACI-1550487, ACI-1550547, and ACI-1550593

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