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Whats a VAE? : r StableDiffusion - Reddit A VAE is a variational autoencoder An autoencoder is a model (or part of a model) that is trained to produce its input as output By giving the model less information to represent the data than the input contains, it's forced to learn about the input distribution and compress the information
Stable Diffusion BASICS - A guide to VAE : r StableDiffusion trueYou seem to have some misconceptions when it comes to VAE The VAE is what gets you from latent space to pixelated images and vice versa There's hence no such thing as "no VAE" as you wouldn't have an image It hence would have used a default VAE, in most cases that would be the one used for SD 1 5 A VAE is hence also definitely not a "network extension" file Still one of the best ways
What is VAE? : r StableDiffusion - Reddit A VAE extends this concept by making the middle part, or the zip file probabilistic instead of simply flat encoded data at rest A little bit of an mathematical annoyance, but it makes it more robust to corruption and other stuff
GAN 和 VAE 的本质区别是什么？为什么两者总是同时被提起？ 最后说一下比较有意思的事： VAE、GAN、Flow (NICE)三种模型都是2013-2014年提出来的（VAE是13年放到arXiv上的，后来中了NIPS；GAN也同时中了NIPS，而NICE最早是14年的一个ICLR workshop）。 最后的发展情况是：GAN最火，VAE次之，Flow模型似乎总是要火不火。
How should I avoid this problem? Running out of memory vae . . . - Reddit The warning suggests that you replace the VAE Decode node with the VAE Decode Tiled version and try re-running the workflow If it had run out of memory earlier in the workflow it might have also recommended the VAE Encode Tiled node
[D] Is VAE still worth it? : r MachineLearning - Reddit The "VAE" in the context of latent diffusion isn't really a VAE It's more like a glorified downsample-upsample model I mean that's kind of what a VAE is to begin with The encoder downsamples, or compresses, to a bottleneck layer, and the decoder upsamples, or decompresses, back to image space