Learning Hierarchical Variational Autoencoders with Mutual Information Maximization for Autoregressive Sequence Modeling.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2022.3160509
Abstract: Variational autoencoders (VAEs) are a class of effective deep generative models, with the objective to approximate the true, but unknown data distribution. VAEs make use of latent variables to capture high-level semantics so as to… read more here.
Keywords: mutual information; variational autoencoders; sequence; posterior collapse ... See more keywords