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Deep Residual Learning for Nonlinear Regression
Deep learning plays a key role in the recent developments of machine learning. This paper develops a deep residual neural network (ResNet) for the regression of nonlinear functions. Convolutional layers and pooling layers are replaced by fully connected layers in the residual block. To evaluate the...
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| Publicado no: | Entropy (Basel) |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7516619/ https://ncbi.nlm.nih.gov/pubmed/33285968 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e22020193 |
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