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Results tagged with variational-bayes
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user 271843
Variational Bayesian methods approximate intractable integrals found in Bayesian inference and machine learning. Primarily, these methods serve one of two purposes: Approximating the posterior distribution, or bounding the marginal likelihood of observed data.
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Murphy: A probabilistic perspective - Completing the in Variational Inference [duplicate]
I don't understand how bishop derives the fact that $q_{\mu}(\mu)$ follows a gaussian distribution by completing the square. On page 774 of the book, a probabilistic perspective, he says the following …
- 237
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Bishop derivation completing the square in variational inference
I don't understand the derivation on page 467. Bishop says:
Given the optimal factor $q_1^*(z_1)$
\begin{equation}
ln~q_1(z_1) = -\frac{1}{2} z_1^2 \Lambda_{11} + z_1 \mu_1 \Lambda_{11} - z_1 \Lambda …
- 237