Matches in SemOpenAlex for { <https://semopenalex.org/work/W3020191331> ?p ?o ?g. }
- W3020191331 abstract "We perform a comprehensive numerical study of the effect of approximation-theoretical results for neural networks on practical learning problems in the context of numerical analysis. As the underlying model, we study the machine-learning-based solution of parametric partial differential equations. Here, approximation theory predicts that the performance of the model should depend only very mildly on the dimension of the parameter space and is determined by the intrinsic dimension of the solution manifold of the parametric partial differential equation. We use various methods to establish comparability between test-cases by minimizing the effect of the choice of test-cases on the optimization and sampling aspects of the learning problem. We find strong support for the hypothesis that approximation-theoretical effects heavily influence the practical behavior of learning problems in numerical analysis." @default.
- W3020191331 created "2020-05-01" @default.
- W3020191331 creator A5008776954 @default.
- W3020191331 creator A5019220707 @default.
- W3020191331 creator A5027395961 @default.
- W3020191331 creator A5041074956 @default.
- W3020191331 creator A5090767423 @default.
- W3020191331 date "2020-04-25" @default.
- W3020191331 modified "2023-10-01" @default.
- W3020191331 title "Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks" @default.
- W3020191331 cites W1522301498 @default.
- W3020191331 cites W1605528072 @default.
- W3020191331 cites W2047278710 @default.
- W3020191331 cites W2052690618 @default.
- W3020191331 cites W2056653303 @default.
- W3020191331 cites W2070980742 @default.
- W3020191331 cites W2075646404 @default.
- W3020191331 cites W2079224763 @default.
- W3020191331 cites W2117302185 @default.
- W3020191331 cites W2133041109 @default.
- W3020191331 cites W2165695298 @default.
- W3020191331 cites W2166116275 @default.
- W3020191331 cites W2212370034 @default.
- W3020191331 cites W2267743026 @default.
- W3020191331 cites W2295099209 @default.
- W3020191331 cites W2515829451 @default.
- W3020191331 cites W2528305538 @default.
- W3020191331 cites W2550848904 @default.
- W3020191331 cites W2734689136 @default.
- W3020191331 cites W2749028154 @default.
- W3020191331 cites W2753962198 @default.
- W3020191331 cites W2760972773 @default.
- W3020191331 cites W2766298346 @default.
- W3020191331 cites W2772097715 @default.
- W3020191331 cites W2786232134 @default.
- W3020191331 cites W2787302432 @default.
- W3020191331 cites W2803629276 @default.
- W3020191331 cites W2805915852 @default.
- W3020191331 cites W2883486956 @default.
- W3020191331 cites W2889523591 @default.
- W3020191331 cites W2890291741 @default.
- W3020191331 cites W2890889625 @default.
- W3020191331 cites W2903926864 @default.
- W3020191331 cites W2930017973 @default.
- W3020191331 cites W2933916181 @default.
- W3020191331 cites W2962761333 @default.
- W3020191331 cites W2963112935 @default.
- W3020191331 cites W2963146412 @default.
- W3020191331 cites W2963798430 @default.
- W3020191331 cites W2966419255 @default.
- W3020191331 cites W2974910615 @default.
- W3020191331 cites W2981405625 @default.
- W3020191331 cites W2986795381 @default.
- W3020191331 cites W2990653417 @default.
- W3020191331 cites W2998847955 @default.
- W3020191331 cites W2998882635 @default.
- W3020191331 cites W3000236721 @default.
- W3020191331 cites W3002607072 @default.
- W3020191331 cites W3011579803 @default.
- W3020191331 cites W3014009018 @default.
- W3020191331 cites W3023241366 @default.
- W3020191331 cites W3047451562 @default.
- W3020191331 cites W3101643101 @default.
- W3020191331 cites W3103239355 @default.
- W3020191331 cites W3104183394 @default.
- W3020191331 cites W3126658681 @default.
- W3020191331 cites W595079961 @default.
- W3020191331 cites W597932189 @default.
- W3020191331 hasPublicationYear "2020" @default.
- W3020191331 type Work @default.
- W3020191331 sameAs 3020191331 @default.
- W3020191331 citedByCount "11" @default.
- W3020191331 countsByYear W30201913312019 @default.
- W3020191331 countsByYear W30201913312020 @default.
- W3020191331 countsByYear W30201913312021 @default.
- W3020191331 crossrefType "posted-content" @default.
- W3020191331 hasAuthorship W3020191331A5008776954 @default.
- W3020191331 hasAuthorship W3020191331A5019220707 @default.
- W3020191331 hasAuthorship W3020191331A5027395961 @default.
- W3020191331 hasAuthorship W3020191331A5041074956 @default.
- W3020191331 hasAuthorship W3020191331A5090767423 @default.
- W3020191331 hasConcept C105795698 @default.
- W3020191331 hasConcept C111030470 @default.
- W3020191331 hasConcept C114614502 @default.
- W3020191331 hasConcept C117251300 @default.
- W3020191331 hasConcept C126255220 @default.
- W3020191331 hasConcept C134306372 @default.
- W3020191331 hasConcept C151730666 @default.
- W3020191331 hasConcept C154945302 @default.
- W3020191331 hasConcept C197947376 @default.
- W3020191331 hasConcept C202444582 @default.
- W3020191331 hasConcept C2779343474 @default.
- W3020191331 hasConcept C28826006 @default.
- W3020191331 hasConcept C30732413 @default.
- W3020191331 hasConcept C33676613 @default.
- W3020191331 hasConcept C33923547 @default.
- W3020191331 hasConcept C41008148 @default.
- W3020191331 hasConcept C50644808 @default.
- W3020191331 hasConcept C86803240 @default.
- W3020191331 hasConcept C93779851 @default.