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 …

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 …

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 …

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 …

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 …

Dec 15, 2020 · Why is the decoder in an autoencoder uses a sigmoid on the last layer? Asked 5 years, 2 months ago Modified 4 years, 1 month ago Viewed 7k times

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). …

Aug 30, 2023 · Debugging autoencoder training (loss is low but reconstructed image is all black) Asked 2 years, 5 months ago Modified 2 years, 5 months ago Viewed 925 times

Feb 12, 2019 · I have an autoencoder and I checked the accuracy of my model with different solutions like changing the number of conv layer and increase them, add or remove Batch …

Nov 24, 2016 · The deep-learning autoencoder is always unsupervised learning. The "supervised" part of the article you link to is to evaluate how well it did. The following example (taken from …