Lauri Väre

Learn More
We consider the problem of regression on multivariate count data and present a Gibbs sampler for a latent feature regression model suitable for both under-and overdispersed response variables. The model learns count-valued latent features conditional on arbitrary covariates, modeling them as negative binomial variables, and maps them into the dependent(More)
  • 1