How UNET is different from simple autoencoders? - Stack Overflow
Feb 3, 2021 · UNET architecture is like first half encoder and second half decoder . There are different variations of autoencoders like sparse , variational etc. They all compress and …
Why my autoencoder model is not learning? - Stack Overflow
Apr 15, 2020 · If you want to create an autoencoder you need to understand that you're going to reverse process after encoding. That means that if you have three convolutional layers with …
Extract encoder and decoder from trained autoencoder
Sep 11, 2018 · Use this best model (manually selected by filename) and plot original image, the encoded representation made by the encoder of the autoencoder and the prediction using the …
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 …
What is the difference between an autoencoder and an encoder …
Jun 18, 2019 · I want to know if there is a difference between an autoencoder and an encoder-decoder.
neural network - How can autoencoders be used for clustering?
1 Before asking 'how can autoencoder be used to cluster data?' we must first ask 'Can autoencoders cluster data?' Since an autoencoder learns to recreate the data points from the …
Reconstruction error per feature for autoencoders? - Stack Overflow
May 8, 2023 · Usually, autoencoders are symmetric structures so you can reproduce a decoder equivalent to the encoder. A great resource for learning autoencoder is Deep Learning book …
What is an autoencoder? - Data Science Stack Exchange
Aug 17, 2020 · The autoencoder then works by storing inputs in terms of where they lie on the linear image of . Observe that absent the non-linear activation functions, an autoencoder …
convolution - How to implement a 1D Convolutional Auto …
Mar 15, 2018 · The input to the autoencoder is then --> (730,128,1) But when I plot the original signal against the decoded, they are very different!! Appreciate your help on this.
Does attention make sense for Autoencoders? - Stack Overflow
The answer depends very much on what you aim to use the representation from the autoencoder for. Each autoencoder needs something that makes the autoencoding task hard, so it needs a …