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Discovering Nonlinear Static Relationships in Unlabeled Dataset using Autoencoder with Ordered Variance
arXiv:2402.14031v2 Announce Type: replace Abstract: This paper presents an autoencoder with ordered variance (AEO), in which the conventional reconstruction loss is augmented by a variance-based regularization term that promotes an ordered structure within the latent space. In this structure, the latent variables are ordered by their variance computed over the training data, facilitating systematic determination of the latent space dimensionality. The AEO is further extended using residual...