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 …
python - Reducing Losses of Autoencoder - Stack Overflow
May 26, 2020 · Because you are forcing the encoder to represent an information of higher dimension with an information with lower dimension. So the lower the latent dimension is, the …
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 …
python 2.7 - keras autoencoder vs PCA - Stack Overflow
I am playing with a toy example to understand PCA vs keras autoencoder I have the following code for understanding PCA: import numpy as np import matplotlib.pyplot as plt from …
How is a linear autoencoder equal to PCA? - Stack Overflow
Mar 5, 2017 · Autoencoder: Is the decoder the mirrored version of the encoder? 2. Accessing reduced dimensionality of ...
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 ...
how to improve the accuracy of autoencoder? - Stack Overflow
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 …
Autoencoder: using cosine distance as loss function
Sep 10, 2019 · Hey so the Keras implementation of Cosine Similarity is called as Cosine Proximity. It just has one small change, that being cosine proximity = -1*(Cosine Similarity) of …
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 …
machine learning - Is there any sense to use autoencoder for …
Dec 9, 2016 · You train the second autoencoder without touching the first autoencoder. This helps to keep the number of parameters low, and thus makes training simpler and faster. After …