BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling

With the introduction of the variational autoencoder (V AE), probabilistic latent variable models have received renewed attention as powerful generative models. However, their performance in terms of test likelihood and quality of generated samples has been surpassed by autoregressive models without stochastic units. Furthermore, flow-based models have recently been shown to be an attractive alternative that scales well to high-dimensional data.