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Variational Autoencoders (VAE) Theory

A Variational Autoencoder (VAE) is a probabilistic autoencoder that learns to generate data by inferring hidden causes (latent variables) and decoding them back to observations.

#variational autoencoder#elbo#kl divergence+12
📚TheoryIntermediate

Maximum Likelihood & Generative Models

Maximum Likelihood Estimation (MLE) picks parameters that make the observed data most probable under a chosen probabilistic model.

#maximum likelihood
Intermediate
Advanced
Filtering by:
#diagonal covariance
Group:
Generative Model Theory
#generative models
#naive bayes
+12