A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music

ICML 2018 Adam RobertsJesse EngelColin RaffelCurtis HawthorneDouglas Eck

The Variational Autoencoder (VAE) has proven to be an effective model for producing semantically meaningful latent representations for natural data. However, it has thus far seen limited application to sequential data, and, as we demonstrate, existing recurrent VAE models have difficulty modeling sequences with long-term structure... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.