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 essentially …
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 …
python - LSTM Autoencoder problems - Stack Overflow
TLDR: Autoencoder underfits timeseries reconstruction and just predicts average value. Question Set-up: Here is a summary of my attempt at a sequence-to-sequence autoencoder. This image was …
python - LSTM Autoencoder - Stack Overflow
Jun 20, 2017 · I'm trying to build a LSTM autoencoder with the goal of getting a fixed sized vector from a sequence, which represents the sequence as good as possible. This autoencoder consists of two …
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 …
Pytorch MNIST autoencoder to learn 10-digit classification
Mar 17, 2021 · Autoencoder is technically not used as a classifier in general. They learn how to encode a given image into a short vector and reconstruct the same image from the encoded vector. It is a …
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 filters in this …
CNN Autoencoder takes a very long time to train - Stack Overflow
Mar 17, 2025 · I have been training a CNN Autoencoder on binary images (pixels are either 0 or 1) of size 64x64. The model is shown below: import torch import torch.nn as nn import torch.nn.functional …
How does binary cross entropy loss work on autoencoders?
Sep 21, 2018 · Note that in the case of input values in range [0,1] you can use binary_crossentropy, as it is usually used (e.g. Keras autoencoder tutorial and this paper). However, don't expect that the loss …
Does it make sense to train a CNN as an autoencoder?
So, does anyone know if I could just pretrain a CNN as if it was a "crippled" autoencoder, or would that be pointless? Should I be considering some other architecture, like a deep belief network, for instance?