2019
Avoiding Latent Variable Collapse with Generative Skip Models
AISTATS 2019poster
Variational autoencoders (VAEs) learn distributions of high-dimensional data. They model data with a deep latent-variable model and then fit the model by maximizing a lower bound of the log marginal likelihood. VAEs can capture complex distributions, but they can also suffer from an issue known as "…