Matches in SemOpenAlex for { <https://semopenalex.org/work/W4206276614> ?p ?o ?g. }
- W4206276614 abstract "In this paper, we introduce VPNet, a novel model-driven neural network architecture based on variable projection (VP). Applying VP operators to neural networks results in learnable features, interpretable parameters, and compact network structures. This paper discusses the motivation and mathematical background of VPNet and presents experiments. The VPNet approach was evaluated in the context of signal processing, where we classified a synthetic dataset and real electrocardiogram (ECG) signals. Compared to fully connected and one-dimensional convolutional networks, VPNet offers fast learning ability and good accuracy at a low computational cost of both training and inference. Based on these advantages and the promising results obtained, we anticipate a profound impact on the broader field of signal processing, in particular on classification, regression and clustering problems." @default.
- W4206276614 created "2022-01-26" @default.
- W4206276614 creator A5007271427 @default.
- W4206276614 creator A5015047710 @default.
- W4206276614 creator A5049116697 @default.
- W4206276614 creator A5052379851 @default.
- W4206276614 date "2021-10-13" @default.
- W4206276614 modified "2023-10-02" @default.
- W4206276614 title "VPNET: Variable Projection Networks" @default.
- W4206276614 cites W1593505867 @default.
- W4206276614 cites W1771018557 @default.
- W4206276614 cites W1849277567 @default.
- W4206276614 cites W1901129140 @default.
- W4206276614 cites W1906770428 @default.
- W4206276614 cites W1970163214 @default.
- W4206276614 cites W1975640002 @default.
- W4206276614 cites W1981211771 @default.
- W4206276614 cites W1981464569 @default.
- W4206276614 cites W1982784722 @default.
- W4206276614 cites W2003186286 @default.
- W4206276614 cites W2006560811 @default.
- W4206276614 cites W2010339367 @default.
- W4206276614 cites W2017487767 @default.
- W4206276614 cites W2018089423 @default.
- W4206276614 cites W2034255538 @default.
- W4206276614 cites W2065288681 @default.
- W4206276614 cites W2067755824 @default.
- W4206276614 cites W2072918376 @default.
- W4206276614 cites W2073416575 @default.
- W4206276614 cites W2076063813 @default.
- W4206276614 cites W2080966422 @default.
- W4206276614 cites W2090636411 @default.
- W4206276614 cites W2091026599 @default.
- W4206276614 cites W2093353308 @default.
- W4206276614 cites W2099284973 @default.
- W4206276614 cites W2100495367 @default.
- W4206276614 cites W2102360888 @default.
- W4206276614 cites W2103308415 @default.
- W4206276614 cites W2148248445 @default.
- W4206276614 cites W2156714229 @default.
- W4206276614 cites W2162800060 @default.
- W4206276614 cites W2163922914 @default.
- W4206276614 cites W2251133041 @default.
- W4206276614 cites W2281090488 @default.
- W4206276614 cites W2291961022 @default.
- W4206276614 cites W2500334604 @default.
- W4206276614 cites W2600297185 @default.
- W4206276614 cites W2604388535 @default.
- W4206276614 cites W2619204584 @default.
- W4206276614 cites W2784187484 @default.
- W4206276614 cites W2786413162 @default.
- W4206276614 cites W2804075771 @default.
- W4206276614 cites W2915772270 @default.
- W4206276614 cites W2921440296 @default.
- W4206276614 cites W2933411141 @default.
- W4206276614 cites W2945285932 @default.
- W4206276614 cites W2964121960 @default.
- W4206276614 cites W2966126335 @default.
- W4206276614 cites W2991513784 @default.
- W4206276614 cites W2997009477 @default.
- W4206276614 cites W3000166127 @default.
- W4206276614 cites W3003600398 @default.
- W4206276614 cites W3009948084 @default.
- W4206276614 cites W3011730771 @default.
- W4206276614 cites W3017101319 @default.
- W4206276614 cites W3017227461 @default.
- W4206276614 cites W3033013105 @default.
- W4206276614 cites W3037862741 @default.
- W4206276614 cites W3039380052 @default.
- W4206276614 cites W3044215473 @default.
- W4206276614 cites W3146685014 @default.
- W4206276614 cites W3178131476 @default.
- W4206276614 cites W3208674021 @default.
- W4206276614 cites W4300402905 @default.
- W4206276614 cites W4320800818 @default.
- W4206276614 cites W4378009855 @default.
- W4206276614 doi "https://doi.org/10.1142/s0129065721500544" @default.
- W4206276614 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34651549" @default.
- W4206276614 hasPublicationYear "2021" @default.
- W4206276614 type Work @default.
- W4206276614 citedByCount "8" @default.
- W4206276614 countsByYear W42062766142021 @default.
- W4206276614 countsByYear W42062766142022 @default.
- W4206276614 countsByYear W42062766142023 @default.
- W4206276614 crossrefType "journal-article" @default.
- W4206276614 hasAuthorship W4206276614A5007271427 @default.
- W4206276614 hasAuthorship W4206276614A5015047710 @default.
- W4206276614 hasAuthorship W4206276614A5049116697 @default.
- W4206276614 hasAuthorship W4206276614A5052379851 @default.
- W4206276614 hasBestOaLocation W42062766141 @default.
- W4206276614 hasConcept C104267543 @default.
- W4206276614 hasConcept C11413529 @default.
- W4206276614 hasConcept C119857082 @default.
- W4206276614 hasConcept C124101348 @default.
- W4206276614 hasConcept C134306372 @default.
- W4206276614 hasConcept C151730666 @default.
- W4206276614 hasConcept C153180895 @default.
- W4206276614 hasConcept C154945302 @default.
- W4206276614 hasConcept C182365436 @default.
- W4206276614 hasConcept C202426404 @default.