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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Detalles Bibliográficos
Autores principales: Chen, Dongwei, Hu, Fei, Nian, Guokui, Yang, Tiantian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516619/
https://www.ncbi.nlm.nih.gov/pubmed/33285968
http://dx.doi.org/10.3390/e22020193

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516619/
https://www.ncbi.nlm.nih.gov/pubmed/33285968
http://dx.doi.org/10.3390/e22020193

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