November 4, 2019 Bachelor Thesis Open Access

Heine, Greta Sophie

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        "affiliation": "KIT/ETP", 
        "name": "Heine, Greta Sophie"
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    "description": "<p>This thesis enhances the understanding of Neural Network (NN) trainings by<br>\ninvestigation of the learning process especially focusing on the dependence<br>\nof the NN output on the input space for given tasks. For this purpose, the<br>\nNN function is decomposed into a Taylor expansion. The Taylor coefficients<br>\nserve as a metric to illustrate the influence of input space features on the<br>\noutput at each step of the training. Both, the arithmetic mean values of the<br>\nTaylor coefficients and their dependence on each point of the input space are<br>\ninvestigated, giving new insights into the decision taking of NNs.</p>", 
    "keywords": [
      "neural network, training, Taylor expansion"
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    "language": "eng", 
    "publication_date": "2019-11-04", 
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      "report_number": "ETP-BACHELOR-KA/2019-17", 
      "supervisors": [
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          "affiliation": "KIT/ETP", 
          "name": "Wolf, Roger"
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        {
          "affiliation": "KIT/ETP", 
          "name": "Quast, Guenther"
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    "title": "Illustration of the Neural Network Learning Process during Training"
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