Poster Open Access

DeepSphere: towards an equivariant graph-based spherical CNN (ICLR'19 RLGM workshop poster)

Defferrard, Michaël; Perraudin, Nathanaël


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  <identifier identifierType="DOI">10.5281/zenodo.2839355</identifier>
  <creators>
    <creator>
      <creatorName>Defferrard, Michaël</creatorName>
      <givenName>Michaël</givenName>
      <familyName>Defferrard</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-6028-9024</nameIdentifier>
      <affiliation>EPFL</affiliation>
    </creator>
    <creator>
      <creatorName>Perraudin, Nathanaël</creatorName>
      <givenName>Nathanaël</givenName>
      <familyName>Perraudin</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-8285-1308</nameIdentifier>
      <affiliation>SDSC</affiliation>
    </creator>
  </creators>
  <titles>
    <title>DeepSphere: towards an equivariant graph-based spherical CNN (ICLR'19 RLGM workshop poster)</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>graph neural networks</subject>
    <subject>geometric deep learning</subject>
    <subject>spherical neural networks</subject>
    <subject>equivariance</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-05-06</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Poster</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/2839355</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="arXiv" relationType="IsSupplementedBy">arXiv:1904.05146</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsSupplementedBy">https://github.com/SwissDataScienceCenter/DeepSphere</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.2839354</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Poster presented at the Representation Learning on Graphs and Manifolds (https://rlgm.github.io) workshop at ICLR&amp;#39;19.&lt;/p&gt;</description>
  </descriptions>
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