Nanopublications

@prefix this: <https://w3id.org/np/RA5aU0Cg0MKc5moV6xOk_ThBwxah5xipXgz6sy0F29N2Q> .
@prefix sub: <https://w3id.org/np/RA5aU0Cg0MKc5moV6xOk_ThBwxah5xipXgz6sy0F29N2Q/> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix nt: <https://w3id.org/np/o/ntemplate/> .
@prefix npx: <http://purl.org/nanopub/x/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix orcid: <https://orcid.org/> .
@prefix ns1: <http://purl.org/np/> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .

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    a np:Nanopublication .
}

sub:assertion {
  sub:assertion dct:creator orcid:0000-0002-1784-2920 ;
    <http://purl.org/spar/cito/includesQuotationFrom> <https://dblp.org/rec/conf/nips/KrizhevskySH12> ;
    rdfs:comment "In abstract: \"On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than the previous state-of-the-art. The neural network, which has 60 million parameters and 650,000 neurons, consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.\"" .
}

sub:provenance {
sub:assertion prov:wasAttributedTo orcid:0000-0002-1784-2920 .
}

sub:pubinfo {
  orcid:0000-0002-1784-2920 foaf:name "Anne Fouilloux" .
  this: dct:created "2025-05-22T10:58:43.659Z"^^xsd:dateTime ;
    dct:creator orcid:0000-0002-1784-2920 ;
    dct:license <https://creativecommons.org/licenses/by/4.0/> ;
    npx:hasNanopubType <http://purl.org/spar/cito/cites> ;
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    rdfs:label "includes quotation from KrizhevskySH12" ;
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