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Stochastic bottleneck
Intermediate layer of VAEs where information is compressed into random variables following probability distributions, unlike the deterministic bottleneck of classical autoencoders.
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Latent sampling
Process of sampling points in the latent space according to the distributions learned by the encoder, enabling the generation of diverse and realistic new data.
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VAE loss function
Composite objective function combining the reconstruction loss (typically mean squared error or binary cross-entropy) and the KL divergence regularization term.
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Stochastic regularization
Inherent mechanism in VAEs that prevents overfitting by forcing latent distributions to remain close to the prior distribution, ensuring a continuous and interpolable latent space.
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