What does "variational" mean? - Cross Validated
Apr 17, 2018 · To precisely answer the question what does "variational" mean, we first review the origins of variational inference. By this approach, we gain a broader understanding of the term's meaning. …
deep learning - When should I use a variational autoencoder as …
Jan 22, 2018 · I understand the basic structure of variational autoencoder and normal (deterministic) autoencoder and the math behind them, but when and why would I prefer one type of autoencoder to …
bayesian - What are variational autoencoders and to what learning …
Jan 6, 2018 · Even though variational autoencoders (VAEs) are easy to implement and train, explaining them is not simple at all, because they blend concepts from Deep Learning and Variational Bayes, …
Understanding the Evidence Lower Bound (ELBO) - Cross Validated
Jun 24, 2022 · I am reading this tutorial about Variational Inference, which includes the following depiction of ELBO as the lower bound on log-likelihood on the third page. In the tutorial, $x_i$ is the …
regression - What is the difference between Variational Inference and ...
Jul 13, 2022 · Many methods proposed for variational inference on latent variable problems alternate between optimizing ηz η z for fixed ηθ η θ and then vice versa, what are known in optimization as …
How to do dimension reduction from a variational autoencoder
Dec 19, 2023 · I am thinking about a variational autoencoder. As far as I understand it, in the encoding section you compress to a px1 tensor and then you create a $\\mu$ and $\\sigma$ of dimensions of …
How to weight KLD loss vs reconstruction loss in variational auto …
Mar 7, 2018 · How to weight KLD loss vs reconstruction loss in variational auto-encoder? Ask Question Asked 7 years, 11 months ago Modified 2 years, 5 months ago
Understanding the set of latent variables $Z$ in variational inference
Mar 4, 2021 · Variational inference approximates this posterior by using the "best" distribution within a family of distributions referred to as the mean-field family: This family is characterised by the fact that …
Why do we use Gaussian distributions in Variational Autoencoder?
Apr 11, 2019 · 21 I still don't understand why we force the distribution of the hidden representation of a Variational Autoencoder (VAE) to follow a multivariate normal distribution. Why this specific …
Normalizing flows as a generalization of variational autoencoders ...
Apr 24, 2021 · Normalizing flows are often introduced as a way of restricting the rigid priors that are placed on the latent variables in Variational Autoencoders. For example, from the Pyro docs: In …