Keywords

#variational_autoencoder

Variational autoencoder

Deep learning generative model to encode data representation

In machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling. It is part of the families of probabilistic graphical models and variational Bayesian methods.

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Variational autoencoder Autoencoder Latent diffusion model Variational Bayesian methods Vision transformer Evidence lower bound Exploration-exploitation dilemma Unsupervised learning Multimodal learning Generative model
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