FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3119228775> ?p ?o ?g. }

• W3119228775 abstract "In this paper we consider utilizing a residual neural network (ResNet) to solve ordinary differential equations. Stochastic gradient descent method is applied to obtain the optimal parameter set of weights and biases of the network. We apply forward Euler, Runge-Kutta2 and Runge-Kutta4 finite difference methods to generate three sets of targets training the ResNet and carry out the target study. The well trained ResNet behaves just as its counterpart of the corresponding one-step finite difference method. In particular, we carry out (1) the architecture study in terms of number of hidden layers and neurons per layer to find the optimal ResNet structure; (2) the target study to verify the ResNet solver behaves as accurate as its finite difference method counterpart; (3) solution trajectory simulation. Even the ResNet solver looks like and is implemented in a way similar to forward Euler scheme, its accuracy can be as high as any one step method. A sequence of numerical examples are presented to demonstrate the performance of the ResNet solver." @default.
• W3119228775 created "2021-01-18" @default.
• W3119228775 creator A5008019619 @default.
• W3119228775 creator A5039437773 @default.
• W3119228775 creator A5045722787 @default.
• W3119228775 creator A5074278814 @default.
• W3119228775 date "2021-01-10" @default.
• W3119228775 modified "2023-10-16" @default.
• W3119228775 title "Accuracy and Architecture Studies of Residual Neural Network solving Ordinary Differential Equations" @default.
• W3119228775 cites W1988115241 @default.
• W3119228775 cites W2027197837 @default.
• W3119228775 cites W2062228129 @default.
• W3119228775 cites W2072128103 @default.
• W3119228775 cites W2076110561 @default.
• W3119228775 cites W2098398123 @default.
• W3119228775 cites W2103496339 @default.
• W3119228775 cites W2105566270 @default.
• W3119228775 cites W2158581396 @default.
• W3119228775 cites W2163605009 @default.
• W3119228775 cites W2166116275 @default.
• W3119228775 cites W2194775991 @default.
• W3119228775 cites W2549139847 @default.
• W3119228775 cites W2591722035 @default.
• W3119228775 cites W2749028154 @default.
• W3119228775 cites W2765128778 @default.
• W3119228775 cites W2782210340 @default.
• W3119228775 cites W2887383111 @default.
• W3119228775 cites W2892393161 @default.
• W3119228775 cites W2899283552 @default.
• W3119228775 cites W2912389156 @default.
• W3119228775 cites W2919115771 @default.
• W3119228775 cites W2944808962 @default.
• W3119228775 cites W2946660403 @default.
• W3119228775 cites W2946866513 @default.
• W3119228775 cites W2951629468 @default.
• W3119228775 cites W2963302407 @default.
• W3119228775 cites W2963359731 @default.
• W3119228775 cites W2963480765 @default.
• W3119228775 cites W2964137095 @default.
• W3119228775 cites W2966903779 @default.
• W3119228775 cites W2973004389 @default.
• W3119228775 cites W2974916071 @default.
• W3119228775 cites W2989600087 @default.
• W3119228775 cites W2997166519 @default.
• W3119228775 cites W3043197282 @default.
• W3119228775 cites W3094089654 @default.
• W3119228775 cites W3098011980 @default.
• W3119228775 cites W3098175809 @default.
• W3119228775 cites W3099423575 @default.
• W3119228775 cites W3101260193 @default.
• W3119228775 cites W3105919389 @default.
• W3119228775 cites W3125537303 @default.
• W3119228775 doi "https://doi.org/10.48550/arxiv.2101.03583" @default.
• W3119228775 hasPublicationYear "2021" @default.
• W3119228775 type Work @default.
• W3119228775 sameAs 3119228775 @default.
• W3119228775 citedByCount "1" @default.
• W3119228775 countsByYear W31192287752023 @default.
• W3119228775 crossrefType "posted-content" @default.
• W3119228775 hasAuthorship W3119228775A5008019619 @default.
• W3119228775 hasAuthorship W3119228775A5039437773 @default.
• W3119228775 hasAuthorship W3119228775A5045722787 @default.
• W3119228775 hasAuthorship W3119228775A5074278814 @default.
• W3119228775 hasBestOaLocation W31192287751 @default.
• W3119228775 hasConcept C11413529 @default.
• W3119228775 hasConcept C121332964 @default.
• W3119228775 hasConcept C126255220 @default.
• W3119228775 hasConcept C127413603 @default.
• W3119228775 hasConcept C1276947 @default.
• W3119228775 hasConcept C134306372 @default.
• W3119228775 hasConcept C13662910 @default.
• W3119228775 hasConcept C146978453 @default.
• W3119228775 hasConcept C153258448 @default.
• W3119228775 hasConcept C154945302 @default.
• W3119228775 hasConcept C155512373 @default.
• W3119228775 hasConcept C177264268 @default.
• W3119228775 hasConcept C181582579 @default.
• W3119228775 hasConcept C199360897 @default.
• W3119228775 hasConcept C2776637919 @default.
• W3119228775 hasConcept C2778112365 @default.
• W3119228775 hasConcept C2778770139 @default.
• W3119228775 hasConcept C28826006 @default.
• W3119228775 hasConcept C2944601119 @default.
• W3119228775 hasConcept C33923547 @default.
• W3119228775 hasConcept C38409319 @default.
• W3119228775 hasConcept C41008148 @default.
• W3119228775 hasConcept C50644808 @default.
• W3119228775 hasConcept C51544822 @default.
• W3119228775 hasConcept C54355233 @default.
• W3119228775 hasConcept C62884695 @default.
• W3119228775 hasConcept C75380026 @default.
• W3119228775 hasConcept C768646 @default.
• W3119228775 hasConcept C78045399 @default.
• W3119228775 hasConcept C86803240 @default.
• W3119228775 hasConceptScore W3119228775C11413529 @default.
• W3119228775 hasConceptScore W3119228775C121332964 @default.
• W3119228775 hasConceptScore W3119228775C126255220 @default.
• W3119228775 hasConceptScore W3119228775C127413603 @default.
• W3119228775 hasConceptScore W3119228775C1276947 @default.
• W3119228775 hasConceptScore W3119228775C134306372 @default.

• next