This event is part of Uncertainty Quantification and AI for Complex Systems View Details

Experimental Design, Sampling, and Optimization Strategies in Uncertainty Quantification

Description

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This workshop will focus on the statistical design of computer experiments, Monte Carlo sampling methods, Bayesian approximate inference, and optimization solutions for UQ problems.

Organizers

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M A
Mihai Anitescu Argonne National Laboratory
D G
David Ginsbourger University of Bern
F H
Fred Hickernell Illinois Institute of Technology
S L
Shiwei Lan Arizona State University
D S
Daniel Sanz-Alonso University of Chicago
D W
Dave Woods University of Southampton
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