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 | 994 | 994 |
Downloads | 526 | 526 |
Data volume | 3.2 GB | 3.2 GB |
Unique views | 487 | 487 |
Unique downloads | 114 | 114 |