Convolutional neural network based hierarchical autoencoder for nonlinear mode decomposition of fluid field data
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DOI: 10.1063/5.0020721
Abstract: We propose a customized convolutional neural network based autoencoder called a hierarchical autoencoder, which allows us to extract nonlinear autoencoder modes of flow fields while preserving the contribution order of the latent vectors. As preliminary… read more here.
Keywords: order; field; autoencoder; convolutional neural ... See more keywords