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Contractive Autoencoder (CAE) The theory powering a contractive autoencoder, proposed by Rifai et al. [90], is to make the autoencoders robust of modest adjustments while in the training dataset. In its aim operate, a CAE involves an explicit regularizer that forces the model to learn an encoding that is powerful to smaller adjustments in input val

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