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Unlike traditional AE models, Variational Autoencoders (VAEs) map inputs to a multivariate normal distribution, allowing novel data generation through various sampling methods. The sampling methods covered in this article are posterior sampling, prior sampling, interpolation between two vectors, and latent dimension traversal.


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