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DUNN__MD_292677547454_001

Title
A single sentence description.
A dropout uncertainty neural network (DUNN) model driver v001
Description A dropout uncertainty neural network (DUNN) potential model driver, which supports running in both fully-connected mode and dropout mode. The DUNN can be used easily to quantify the uncertainty in atomistic simulations and determine the transferability of potential.
Disclaimer
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None
Contributor Mingjian Wen
Maintainer Mingjian Wen
Developer Mingjian Wen
Ellad B. Tadmor
Published on KIM 2026
How to Cite

This Model Driver originally published in [1] is archived in OpenKIM [2-4].

[1] Wen M, Tadmor EB. Uncertainty quantification in molecular simulations with dropout neural network potentials. npj Computational Materials. 2020;6(1). doi:10.1038/s41524-020-00390-8 — (Primary Source) A primary source is a reference directly related to the item documenting its development, as opposed to other sources that are provided as background information.

[2] Wen M, Tadmor EB. A dropout uncertainty neural network (DUNN) model driver v001. OpenKIM; 2026. doi:10.25950/ae3fd4ae

[3] Tadmor EB, Elliott RS, Sethna JP, Miller RE, Becker CA. The potential of atomistic simulations and the Knowledgebase of Interatomic Models. JOM. 2011;63(7):17. doi:10.1007/s11837-011-0102-6

[4] Elliott RS, Tadmor EB. Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API). OpenKIM; 2011. doi:10.25950/ff8f563a

Funding Not available
Short KIM ID
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MD_292677547454_001
Extended KIM ID
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DUNN__MD_292677547454_001
DOI 10.25950/ae3fd4ae
https://doi.org/10.25950/ae3fd4ae
https://commons.datacite.org/doi.org/10.25950/ae3fd4ae
KIM Item TypeModel Driver
KIM API Version2.3
Programming Language(s)
The programming languages used in the code and the percentage of the code written in each one.
96.41% C++
2.44% Shell
1.15% TeX
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