A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations. | D2R Server publishing the DBLP Bibliography Database, hosted at L3S Research Center

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dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Arnulf_Jentzen>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Fabian_Hornung>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Philipp_Grohs>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Philippe_von_Wurstemberger>
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dcterms:issued	2018 (xsd:gYear)
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rdfs:label	A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations. (xsd:string)
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foaf:maker	<https://dblp.l3s.de/d2r/resource/authors/Philipp_Grohs>
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dc:title	A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations. (xsd:string)
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