Analysis of neural networks. Applications to interpretability and uncertainty

dc.contributor.advisorBenseny, Antoni
dc.contributor.advisorRubio Muñoz, Alberto
dc.contributor.authorMarín Sánchez, Gabriel
dc.date.accessioned2021-06-01T07:12:51Z
dc.date.available2021-06-01T07:12:51Z
dc.date.issued2020-06-22
dc.descriptionTreballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2020, Director: Antoni Benseny i Alberto Rubio Muñozca
dc.description.abstract[en] From image creation and pattern recognition to speech and text processing, the outstanding performance of neural networks in a wide variety of fields has made them a popular tool among researchers. However, the fact that we do not fully understand why their performance is so successful or how they operate converts this technology into a black-box model based on trial and error. In this work, we attempt to give deep neural networks a mathematical representation and present different examples and applications that bring light to the understanding of neural networks’ behaviour and usage.ca
dc.format.extent56 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/177854
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Gabriel Marín Sánchez, 2020
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Matemàtiques
dc.subject.classificationIntel·ligència artificialca
dc.subject.classificationTreballs de fi de grau
dc.subject.classificationXarxes neuronals (Informàtica)ca
dc.subject.classificationSistemes experts (Informàtica)ca
dc.subject.otherArtificial intelligenceen
dc.subject.otherBachelor's theses
dc.subject.otherNeural networks (Computer science)en
dc.subject.otherExpert systems (Computer science)en
dc.titleAnalysis of neural networks. Applications to interpretability and uncertaintyca
dc.typeinfo:eu-repo/semantics/bachelorThesisca

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