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Data · dataset · 2022

Scripts and Models for "Predicting electronic structures at any length scale with machine learning"

Listed in RODARE

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".

Description

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 |

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Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
RODARE185113 d agoJSON v1
FieldAssertionExtractorEvidence
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