text: Here , we leverage a logistic stick-breaking representation and recent innovations in Pólya-gamma augmentation to reformu-late the << multinomial distribution >> in terms of [[ latent variables ]] with jointly Gaussian likelihoods , enabling us to take advantage of a host of Bayesian inference techniques for Gaussian models with minimal overhead .