bayesian - What are variational autoencoders and to what learning …
Jan 6, 2018 · 37 As per this and this answer, autoencoders seem to be a technique that uses neural networks for dimension reduction. I would like to additionally know what is a variational autoencoder …
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 …
Variational Autoencoder − Dimension of the latent space
And in a variational autoencoder, each feature is actually a sliding scale between two distinct versions of a feature, e.g. male/female for faces, or wide/thin brushstroke for MNIST digits. Can you think of just …
Normalizing flows as a generalization of variational autoencoders ...
Apr 24, 2021 · So the base distribution used is a Gaussian, same as in Variational Autoencoders? To summarize, I have read the statement that normalizing flows somehow "relax" the limitations of …
Image generation using autoencoder vs. variational autoencoder
Sep 17, 2021 · I think that the autoencoder (AE) generates the same new images every time we run the model because it maps the input image to a single point in the latent space. On the other hand, the …
Smartest way to add KL Divergence into (Variational) Auto Encoder
Oct 6, 2020 · Smartest way to add KL Divergence into (Variational) Auto Encoder Asked 5 years, 4 months ago Modified 5 years, 4 months ago Viewed 2k times
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 …
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
keras variational autoencoder loss function - Stack Overflow
From appendix C in the original variational autoencoder paper: In variational auto-encoders, neural networks are used as probabilistic encoders and decoders. There are many possible choices of …
Help Understanding Reconstruction Loss In Variational Autoencoder
Help Understanding Reconstruction Loss In Variational Autoencoder Ask Question Asked 8 years ago Modified 5 years, 7 months ago