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Research data supporting "Learning Models for Electron Densities with Bayesian Regression"

Repository URI

https://www.repository.cam.ac.uk/handle/1810/274113

Repository DOI

https://doi.org/10.17863/CAM.14349
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Files

Primary README.txt (1.97 KB)
 error_estimates.pckl (2.99 MB)
 Al_compression_curves_Profess.zip (9.53 MB)
 SWCNT_electron_densities.zip (4.61 MB)
 various_compression_curves_castep.zip (440.96 KB)

Type

Dataset

Change log

Authors

Description

The data for the reconstruction of the images shown in the paper is contained in *.pckl files. These files were created using Python's pickle module: https://docs.python.org/3.5/library/pickle.html

Version

Software / Usage instructions

In order to use the provided files Python and the pickle module are required. The regression were done using the Python module PottyTrainer developed for this paper and also linked in the paper.

Keywords

Embedded Atom Method, Bayes, Linear Regression, Density Functional Theory, Regression data

Publisher

Rights and licensing

Attribution 4.0 International (CC BY 4.0)
Except where otherwised noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)
Sponsorship
EPSRC (1369467)
Engineering and Physical Sciences Research Council (EP/L015552/1)

Relationships

Supplements:
https://www.repository.cam.ac.uk/handle/1810/276536
https://doi.org/10.1016/j.commatsci.2018.03.029

Collections

Research Data - Materials Science and Metallurgy