Reliability and reproducibility in computational science: implementing validation, verification and uncertainty quantification in silico-Reference-Cited by-同舟云学术

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Reliability and reproducibility in computational science: implementing validation, verification and uncertainty quantification in silico

Published:2021-03-29 Issue:2197 Volume:379 Page:
ISSN:1364-503X
Container-title:Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
language:en
Short-container-title:Phil. Trans. R. Soc. A.

Author:

Coveney Peter V.¹^ORCID,Groen Derek²^ORCID,Hoekstra Alfons G.³^ORCID

Affiliation:

1. Centre for Computational Science, University College London, Gordon Street, London, UK

2. Department of Computer Science, Brunel University London, London, UK

3. Institute for Informatics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, Netherlands

Funder

European Commission

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Link

https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2020.0409

Reference14 articles.

1. Learning from reproducing computational results: introducing three principles and the Reproduction Package

2. Reproducible validation and replication studies in nanoscale physics

3. The importance of uncertainty quantification in model reproducibility

4. Towards validated multiscale simulations for fusion

5. Uncertainty quantification in classical molecular dynamics

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