From c55f09dfcb38ec850d2dc839d8225a4ab1b01fe0 Mon Sep 17 00:00:00 2001 From: Yuchen Pei Date: Thu, 14 Feb 2019 10:29:45 +0100 Subject: minor --- posts/2019-02-14-raise-your-elbo.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/posts/2019-02-14-raise-your-elbo.md b/posts/2019-02-14-raise-your-elbo.md index 18c085b..5b789aa 100644 --- a/posts/2019-02-14-raise-your-elbo.md +++ b/posts/2019-02-14-raise-your-elbo.md @@ -550,7 +550,7 @@ this section). But now both $\pi$ and $\eta$ are random variables. Let the prior distribution $p(\pi)$ is Dirichlet with parameter $(\alpha, \alpha, ..., \alpha)$. Let the prior $p(\eta_k)$ be the conjugate prior of $(x | \eta_k)$, with parameter $\beta$, we will see -later in this section that the posterior $q(\eta_k)$ has belongs to the +later in this section that the posterior $q(\eta_k)$ belongs to the same family as $p(\eta_k)$. Represented in a plate notations, a fully Bayesian mixture model looks like: -- cgit v1.2.3