Scripts and models for "Machine learning the electronic structure of matter across temperatures"
Scripts and models for "Machine learning the electronic structure of matter across temperatures"
Fiedler, L.; Modine, N. A.; Miller, K. D.; Cangi, A.
# Data and Scripts for "Machine learning the electronic structure of matter across temperatures" This dataset contains data and calculation scripts for the publication "Machine learning the electronic structure of matter across temperatures". Its goal is to enable interested parties to reproduce the experiments we have carried out. ## Prerequesites The following software versions are needed for the python scripts: - `python`: 3.8.x - `mala`: 1.2.0 - `numpy`: 1.23.0 (lower version may work) Further, make sure you have downloaded additional data such as local pseudopotentials and training data. ## Contents - `data_analysis/`: Contains scripts contain useful functions to reproduce the analysis carried out on the provided data. - `model_training/`: Contains scripts that allow the training and testing of the models discussed in the accompanying publication. - `trained_models`: Contains the models discussed in the accompanying publication. Per data set, five models with different random initializations were trained.
Related publications
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Machine learning the electronic structure of matter across temperatures
ROBIS: 37111 has used this (Id 36845) publication of HZDR-primary research data
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Reseach data in the HZDR data repository RODARE
Publication date: 2023-04-20 Open access
DOI: 10.14278/rodare.2265
Versions: 10.14278/rodare.2266
License: CC-BY-4.0
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Permalink: https://www.hzdr.de/publications/Publ-36845
Publ.-Id: 36845