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Results tagged with variational-bayes
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user 215872
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.
2
votes
1
answer
267
views
Variational Inference - deriving coordinate update equations for mixture model
I'm currently going through this paper by Blei et. al. that describes the setup and derivation of the coordinate ascent equations for a Gaussian mixture model with K components. I am having some trou …
10
votes
Accepted
What's a mean field variational family?
Loosely speaking, the mean field family defines a specific class of joint distributions. So $z$ here is actually a parameter vector of length m. That means that $q(z)$ describes a joint distribution …
1
vote
Accepted
Confusion on terminology for a variational autoencoder
The prior and posterior distributions are distributions over your parameters/latent variables, not your data. So in this case, the prior would be $p(z)$, and the posterior is $p(z|x)$.
I have never …