@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://search.nfdi4chem.de/dataset/doi-10-18419-darus-2136> a dcat:Dataset ;
    dct:description "Code and documentation for the improved Gaussian Moments Neural Network (GM-NN). An updated version can be found <a href=\"https://gitlab.com/zaverkin_v/gmnn\">on GitLab</a>" ;
    dct:identifier <https://doi.org/10.18419/darus-2136> ;
    dct:issued "2023-05-08T19:13:34.100886"^^xsd:dateTime ;
    dct:modified "2023-05-08T19:13:34.100892"^^xsd:dateTime ;
    dct:publisher <https://search.nfdi4chem.de/organization/9a7d2a53-21f6-412a-afb9-a15122df0640> ;
    dct:title "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "DaRUS" ] ;
    dcat:distribution <https://search.nfdi4chem.de/dataset/doi-10-18419-darus-2136/resource/220d0422-e9e1-4c76-9031-9c638bd7dfd4> ;
    dcat:keyword "atomistic-machine-learning",
        "chemistry",
        "computational-chemistry",
        "computer-and-information-science",
        "gaussian-moments",
        "gm-nn",
        "physics",
        "potential-energy-surface" .

<https://search.nfdi4chem.de/dataset/doi-10-18419-darus-2136/resource/220d0422-e9e1-4c76-9031-9c638bd7dfd4> a dcat:Distribution ;
    dct:format "HTML" ;
    dct:issued "2023-05-08T19:13:34.115103"^^xsd:dateTime ;
    dct:modified "2023-05-08T19:13:34.085289"^^xsd:dateTime ;
    dct:title "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments" ;
    dcat:accessURL <https://doi.org/10.18419/darus-2136> .

<https://search.nfdi4chem.de/organization/9a7d2a53-21f6-412a-afb9-a15122df0640> a foaf:Organization ;
    foaf:name "DaRUS" .