Understanding the Evidence Lower Bound (ELBO) - Cross Validated
Jun 24, 2022 · With that in mind, the ELBO can be a meaningful lower bound on the log-likelihood: both are negative, but ELBO is lower. How much lower? The KL divergence from the conditional …
maximum likelihood - ELBO - Jensen Inequality - Cross Validated
Jan 22, 2024 · ELBO is a quantity used to approximate the log marginal likelihood of observed data, after applying Jensen's inequality to the log likelihood leading to the fact that maximizing the ELBO …
Clarification on the ELBO derivation in diffusion Models
Jan 29, 2025 · 3 I am reading a paper about denoising diffusion models and on page 10, it has the following derivation of the ELBO.
Which exact loss do we minimize in a VAE model?
Apr 26, 2022 · 2 Answers Yes, maximizing the ELBO is equivalent to minimizing the negative ELBO. This is a sign convention. You minimize the negative ELBO (also called the variational free energy) …
How does maximizing ELBO in Bayesian neural networks give us the ...
Oct 1, 2022 · In particular the ELBO doesn't feature the true posterior p(w | D) as you don't know it (if you did you wouldn't be trying to approximate it). The dropped term leading to the inequality "gap" …
Derive ELBO for Mixture of Gaussian - Cross Validated
Nov 30, 2023 · We combine the joint density of the latent and observed variables and the mean-field family to form the ELBO for the mixture of Gaussians.
Derive ELBO for Diffusion Models (MHVAE) - Cross Validated
Mar 15, 2025 · I'm trying to derive the ELBO (Evidence Lower Bound) based loss-function used for training Diffusion Models. The following equation (s) are from arXiv:2208.11970 Eq. 43 is written as …
maximum likelihood - VQ-VAE objective - is it ELBO maximization, or ...
Oct 19, 2022 · VQ-VAE objective - is it ELBO maximization, or minimization of the KL-divergence between the posterior and its approximation? Ask Question Asked 3 years, 1 month ago Modified 3 …
ELBO & "backwards" KL divergence argument order
Aug 10, 2024 · Yet on the wikipedia page for the ELBO & on the highly cited paper for Bayes-by-backprop it shows the ELBO using the KL "in reverse" (i.e. true distribution is the second argument):
Why does Variational Inference work? - Cross Validated
Jun 24, 2024 · ELBO is a lower bound, and only matches the true likelihood when the q-distribution/encoder we choose equals to the true posterior distribution. Are there any guarantees …