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| -rw-r--r-- | posts/2019-02-14-raise-your-elbo.md | 2 |
1 files changed, 1 insertions, 1 deletions
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: |