HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals

In this paper, we propose a very simple but effective VAE model (HM-VAE) that can handle real-valued data with heterogeneous marginals, meaning that they have drastically distinct marginal distributions, statistical properties as well as semantics. Preliminary results show that the HM-VAE can learn distributions with heterogeneous marginal distributions, whereas the vanilla VAEs fails.