Variational Autoencoders with Jointly Optimized Latent Dependency Structure | OpenReview

Variational Autoencoders with Jointly Optimized Latent Dependency Structure Sep 27, 2018 Blind Submission readers: everyone Show Bibtex Abstract: We propose a method for learning the dependency structure between latent variables in deep latent variable models. Our general modeling and inference framework combines the complementary strengths of deep generative models and probabilistic graphical models. In particular, we express the latent variable space of a variational autoencoder (VAE) in

Keywords: autoencoder
Date: 2020/01/28 23:21

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