| Title
A single sentence description.
|
A dropout uncertainty neural network (DUNN) model driver v000 |
|---|---|
| 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
A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.
|
None |
| Contributor |
Mingjian Wen |
| Maintainer |
Mingjian Wen |
| Developer |
Mingjian Wen Ellad B. Tadmor |
| Published on KIM | 2019 |
| 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 [2] Wen M, Tadmor EB. A dropout uncertainty neural network (DUNN) model driver v000. OpenKIM; 2019. doi:10.25950/9573ca43 [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 Click here to download the above citation in BibTeX format. |
| Funding | Not available |
| Short KIM ID
The unique KIM identifier code.
| MD_292677547454_000 |
| Extended KIM ID
The long form of the KIM ID including a human readable prefix (100 characters max), two underscores, and the Short KIM ID. Extended KIM IDs can only contain alpha-numeric characters (letters and digits) and underscores and must begin with a letter.
| DUNN__MD_292677547454_000 |
| DOI |
10.25950/9573ca43 https://doi.org/10.25950/9573ca43 https://commons.datacite.org/doi.org/10.25950/9573ca43 |
| KIM Item Type | Model Driver |
| KIM API Version | 2.0 |
| Programming Language(s)
The programming languages used in the code and the percentage of the code written in each one.
| 97.47% C++ 2.53% Shell |
| DUNN_WenTadmor_2019v1_C__MO_584345505904_000 |
| DUNN_WenTadmor_2019v2_C__MO_956135237832_000 |
| DUNN_WenTadmor_2019v3_C__MO_714772088128_000 |
| DUNN__MD_292677547454_000.txz | Tar+XZ | Linux and OS X archive |
| DUNN__MD_292677547454_000.zip | Zip | Windows archive |