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I hope that this clears things up. We have four variables. The mean and variance of the encoder. And the mean and variance of the decoder. These variables can be multidimensional for the multivariate Gaussian, but they are still four variables. Here are some equations to help you understand:
z = mu(x) + sigma(x)*epsilon # reparameterization trick
x' = MU(z) + SIGMA(z)*epsilon
And here is the legend:
x: input
z: sample from the latent, aka sample from the encoder, aka output of mu(x) plus output of sigma(x) with randomness
mu, sigma: encoder neural networks
MU, SIGMA: decoder neural networks
x': output
[[Special:Contributions/46.199.5.20|46.199.5.20]] ([[User talk:46.199.5.20|talk]]) 19:34, 26 December 2024 (UTC)
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