Dataset Open Access
Fiedler, Lenz;
Schmerler, Steve;
Modine, Normand;
Vogel, Dayton J.;
Popoola, Gabriel A.;
Thompson, Aidan;
Rajamanickam, Sivasankaran;
Cangi, Attila
Scripts and Models for "Predicting the Electronic Structure of Matter on Ultra-Large Scales" This data set contains scripts and models to reproduce the results of our manuscript "Physics-informed Machine Learning Models for Scalable Density Functional Theory Calculations". The scripts are supposed to be used in conjunction with the ab-initio data sets also published alongside our research article. Requirements python>=3.7.x mala>=1.1.0 ase numpy Contents | Folder name | Description | |------------------|--------------------------------------------------| | data_analysis/ | Run script for RDF calculations | | model_inference/ | Run script to run inference based on MALA models | | model_training/ | Run script to train MALA models | | trained_models/ | Trained models for beryllium and aluminium |
Name | Size | |
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size_transfer_cleaned.zip
md5:d7e8a25ec24f5273042c1c469c7caae0 |
6.0 MB | Download |
All versions | This version | |
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Views | 833 | 833 |
Downloads | 512 | 512 |
Data volume | 3.1 GB | 3.1 GB |
Unique views | 368 | 368 |
Unique downloads | 100 | 100 |