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  <doc>
    <id>9064</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>624</pageFirst>
    <pageLast>635</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>222</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">On the Activation Space of ReLU Equipped Deep Neural Networks</title>
    <abstract language="eng">Modern Deep Neural Networks are getting wider and deeper in their architecture design. However, with an increasing number of parameters the decision mechanisms becomes more opaque. Therefore, there is a need for understanding the structures arising in the hidden layers of deep neural networks.&#13;
&#13;
In this work, we present a new mathematical framework for describing the canonical polyhedral decomposition in the input space, and in addition, we introduce the notions of collapsing- and preserving patches, pertinent to understanding the forward map and the activation space they induce.&#13;
&#13;
The activation space can be seen as the output of a layer and, in the particular case of ReLU activations, we prove that this output has the structure of a polyhedral complex.</abstract>
    <parentTitle language="eng">Procedia Computer Science</parentTitle>
    <identifier type="doi">10.1016/j.procs.2023.08.200</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Mustafa Chaukair</author>
    <submitter>Ekaterina Engel</submitter>
    <author>Christof Schütte</author>
    <author>Vikram Sunkara</author>
    <collection role="persons" number="schuette">Schütte, Christof</collection>
    <collection role="persons" number="sunkara">Sunkara, Vikram</collection>
    <collection role="projects" number="no-project">no-project</collection>
    <collection role="institutes" number="MSoCP">Modeling and Simulation of Complex Processes</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
</export-example>
