2019
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
ICML 2019oral
We present a non-parametric Bayesian latent variable model capable of learning dependency structures across dimensions in a multivariate setting. Our approach is based on flexible Gaussian process priors for the generative mappings and interchangeable Dirichlet process priors to learn the structure.…