Tweeted By @glouppe

Bayesian recipe of the day 🧑‍🍳: Take a simple latent variable model where the latents are Gaussian and the observed variables are linear Gaussian. Fit the linear projection parameters by maximum likelihood estimation. Then, posterior inference gives you (Probabilistic) PCA! 🤯 pic.twitter.com/lTtKLhvVO0

— Gilles Louppe (@glouppe) October 18, 2022