@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://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-hal-00850436v1> a dcat:Dataset ;
    dct:description """
              We study pathwise invariances of centred random fields that can be controlled through the covariance. A result involving composition operators is obtained in second-order settings, and we show that various path properties including additivity boil down to invariances of the covariance kernel. These results are extended to a broader class of operators in the Gaussian case, via the Loève isometry. Several covariance-driven pathwise invariances are illustrated, including fields with symmetric paths, centred paths, harmonic paths, or sparse paths. The proposed approach delivers a number of promising results and perspectives in Gaussian process regression.
            """ ;
    dct:identifier "hal-00850436" ;
    dct:issued "2026-05-10T03:42:51.498977"^^xsd:dateTime ;
    dct:language "en" ;
    dct:modified "2026-05-10T03:42:51.498983"^^xsd:dateTime ;
    dct:publisher <https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> ;
    dct:title "Invariances of random fields paths, with applications in Gaussian Process Regression" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "CCSD" ] ;
    dcat:distribution <https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-hal-00850436v1/resource/8b8d265b-2087-4c7b-81de-30fb876b0bbc> ;
    dcat:keyword "bayesian-function-learning",
        "composition-operators",
        "covariance-kernels",
        "infoeu-reposemanticspreprint",
        "infoinfo-mocomputer-science-csmodeling-and-simulation",
        "mathmath-prmathematics-mathprobability-mathpr",
        "mathmath-stmathematics-mathstatistics-mathst",
        "preprints-working-papers-",
        "rkhs",
        "statmestatistics-statmethodology-statme",
        "statmlstatistics-statmachine-learning-statml",
        "statthstatistics-statstatistics-theory-statth",
        "structural-priors" ;
    dcat:landingPage <https://hal.science/hal-00850436> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-hal-00850436v1/resource/8b8d265b-2087-4c7b-81de-30fb876b0bbc> a dcat:Distribution ;
    dct:format "HTML" ;
    dct:issued "2026-05-10T03:42:51.500948"^^xsd:dateTime ;
    dct:modified "2026-05-10T03:42:51.485155"^^xsd:dateTime ;
    dct:title "Invariances of random fields paths, with applications in Gaussian Process Regression" ;
    dcat:accessURL <https://hal.science/hal-00850436> .

<https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> a foaf:Agent ;
    foaf:name "test_moissonnage_selune" .

<https://hal.science/hal-00850436> a foaf:Document .