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Supporting data for the paper "Efficient white noise sampling and coupling for multilevel Monte Carlo with non-nested meshes"

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Creator
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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Project manager, Creator
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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Creator
Publisher:
University of Oxford
Publication date:
2018
Spatial coverage:
Oxford
DOI:
Language:
English
Keywords:
Subjects:
Documentation:
The attached files contain the supporting data for the paper "Efficient white noise sampling and coupling for multilevel Monte Carlo with non-nested meshes" by Matteo Croci, Michael B. Giles, Marie E. Rognes and Patrick E. Farrell, as accepted in SIAM/ASA Journal on Uncertainty Quantification on 09 September 2018. See README file for additional information regarding the data.
UUID:
uuid:9086c528-56d9-4a95-92c2-ae91c38ac7bc
Deposit date:
2018-09-19

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