Dataset Open Access
Fiedler, Lenz;
Modine, Normand A.;
Miller, Kyle D.;
Cangi, Attila
# 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.
Name | Size | |
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ml_electronic_temperature_data.zip
md5:1b21a1be318ae355556e9bf7d9d9acb2 |
5.1 GB | Download |
All versions | This version | |
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Views | 307 | 307 |
Downloads | 22 | 22 |
Data volume | 112.2 GB | 112.2 GB |
Unique views | 282 | 282 |
Unique downloads | 22 | 22 |
Fiedler, Lenz, Modine, Normand A., Miller, Kyle D., & Cangi, Attila. (2023). Scripts and models for "Machine learning the electronic structure of matter across temperatures" (Version v1.0.0) [Data set]. Rodare. http://doi.org/10.14278/rodare.2266