Matches in SemOpenAlex for { <https://semopenalex.org/work/W3122305422> ?p ?o ?g. }
- W3122305422 endingPage "017119" @default.
- W3122305422 startingPage "017119" @default.
- W3122305422 abstract "We present a new data-driven model to reconstruct nonlinear flow from spatially sparse observations. The model is a version of a conditional variational auto-encoder (CVAE), which allows for probabilistic reconstruction and thus uncertainty quantification of the prediction. We show that in our model, conditioning on the measurements from the complete flow data leads to a CVAE where only the decoder depends on the measurements. For this reason we call the model as Semi-Conditional Variational Autoencoder (SCVAE). The method, reconstructions and associated uncertainty estimates are illustrated on the velocity data from simulations of 2D flow around a cylinder and bottom currents from the Bergen Ocean Model. The reconstruction errors are compared to those of the Gappy Proper Orthogonal Decomposition (GPOD) method." @default.
- W3122305422 created "2021-02-01" @default.
- W3122305422 creator A5000795700 @default.
- W3122305422 creator A5027906286 @default.
- W3122305422 creator A5068501080 @default.
- W3122305422 creator A5086318788 @default.
- W3122305422 date "2021-01-01" @default.
- W3122305422 modified "2023-10-16" @default.
- W3122305422 title "Semi-conditional variational auto-encoder for flow reconstruction and uncertainty quantification from limited observations" @default.
- W3122305422 cites W1633869374 @default.
- W3122305422 cites W1954793758 @default.
- W3122305422 cites W1965555277 @default.
- W3122305422 cites W1979892370 @default.
- W3122305422 cites W1981119767 @default.
- W3122305422 cites W1994616650 @default.
- W3122305422 cites W1996924649 @default.
- W3122305422 cites W1997126009 @default.
- W3122305422 cites W2009797711 @default.
- W3122305422 cites W2014356541 @default.
- W3122305422 cites W2017257315 @default.
- W3122305422 cites W2053095324 @default.
- W3122305422 cites W2071430351 @default.
- W3122305422 cites W2081656950 @default.
- W3122305422 cites W2091582527 @default.
- W3122305422 cites W2111051539 @default.
- W3122305422 cites W2112796928 @default.
- W3122305422 cites W2120101088 @default.
- W3122305422 cites W2135100707 @default.
- W3122305422 cites W2135184400 @default.
- W3122305422 cites W2136211190 @default.
- W3122305422 cites W2143419558 @default.
- W3122305422 cites W2147800946 @default.
- W3122305422 cites W2147836374 @default.
- W3122305422 cites W2172958760 @default.
- W3122305422 cites W2284702987 @default.
- W3122305422 cites W2294798173 @default.
- W3122305422 cites W2461065068 @default.
- W3122305422 cites W2487200415 @default.
- W3122305422 cites W2505756961 @default.
- W3122305422 cites W2625593736 @default.
- W3122305422 cites W2743656748 @default.
- W3122305422 cites W2764880863 @default.
- W3122305422 cites W2766736793 @default.
- W3122305422 cites W2789729222 @default.
- W3122305422 cites W2835039253 @default.
- W3122305422 cites W2888341016 @default.
- W3122305422 cites W2899283552 @default.
- W3122305422 cites W2907260072 @default.
- W3122305422 cites W2908155528 @default.
- W3122305422 cites W2913340405 @default.
- W3122305422 cites W2922937916 @default.
- W3122305422 cites W2948978827 @default.
- W3122305422 cites W2950309905 @default.
- W3122305422 cites W2963223306 @default.
- W3122305422 cites W2999618553 @default.
- W3122305422 cites W3003131864 @default.
- W3122305422 cites W3004893049 @default.
- W3122305422 cites W3035246486 @default.
- W3122305422 cites W3035295279 @default.
- W3122305422 cites W3036694744 @default.
- W3122305422 cites W3046812802 @default.
- W3122305422 cites W3100345157 @default.
- W3122305422 cites W3101380508 @default.
- W3122305422 cites W3104009841 @default.
- W3122305422 cites W4211189800 @default.
- W3122305422 cites W4250955649 @default.
- W3122305422 doi "https://doi.org/10.1063/5.0025779" @default.
- W3122305422 hasPublicationYear "2021" @default.
- W3122305422 type Work @default.
- W3122305422 sameAs 3122305422 @default.
- W3122305422 citedByCount "12" @default.
- W3122305422 countsByYear W31223054222021 @default.
- W3122305422 countsByYear W31223054222022 @default.
- W3122305422 countsByYear W31223054222023 @default.
- W3122305422 crossrefType "journal-article" @default.
- W3122305422 hasAuthorship W3122305422A5000795700 @default.
- W3122305422 hasAuthorship W3122305422A5027906286 @default.
- W3122305422 hasAuthorship W3122305422A5068501080 @default.
- W3122305422 hasAuthorship W3122305422A5086318788 @default.
- W3122305422 hasBestOaLocation W31223054221 @default.
- W3122305422 hasConcept C101738243 @default.
- W3122305422 hasConcept C105795698 @default.
- W3122305422 hasConcept C108583219 @default.
- W3122305422 hasConcept C11413529 @default.
- W3122305422 hasConcept C121332964 @default.
- W3122305422 hasConcept C121864883 @default.
- W3122305422 hasConcept C154945302 @default.
- W3122305422 hasConcept C158622935 @default.
- W3122305422 hasConcept C28826006 @default.
- W3122305422 hasConcept C32230216 @default.
- W3122305422 hasConcept C33923547 @default.
- W3122305422 hasConcept C38349280 @default.
- W3122305422 hasConcept C41008148 @default.
- W3122305422 hasConcept C49937458 @default.
- W3122305422 hasConcept C57879066 @default.
- W3122305422 hasConcept C62520636 @default.
- W3122305422 hasConceptScore W3122305422C101738243 @default.
- W3122305422 hasConceptScore W3122305422C105795698 @default.