deep learning - When should I use a variational autoencoder as …
Jan 22, 2018 · deep-learning autoencoders variational-bayes See similar questions with these tags.
What're the differences between PCA and autoencoder?
Oct 15, 2014 · Both PCA and autoencoder can do demension reduction, so what are the difference between them? In what situation I should use one over another?
What is the origin of the autoencoder neural networks?
Oct 4, 2016 · The chapter about autoencoders in Ian Goodfellow, Yoshua Bengio and Aaron Courville's Deep Learning book says: The idea of autoencoders has been part of the historical …
neural networks - Why do we need autoencoders? - Cross Validated
Recently, I have been studying autoencoders. If I understood correctly, an autoencoder is a neural network where the input layer is identical to the output layer. So, the neural network tries to pr...
What is the difference between convolutional neural networks ...
The idea is the same as with autoencoders or RBMs - translate many low-level features (e.g. user reviews or image pixels) to the compressed high-level representation (e.g. film genres or …
Choosing activation and loss functions in autoencoder
Jan 4, 2020 · Here is the tutorial: https://blog.keras.io/building-autoencoders-in-keras.html. However, I am confused with the choice of activation and loss for the simple one-layer …
mse - Loss function for autoencoders - Cross Validated
I am experimenting a bit autoencoders, and with tensorflow I created a model that tries to reconstruct the MNIST dataset. My network is very simple: X, e1, e2, d1, Y, where e1 and e2 …
When does my autoencoder start to overfit? - Cross Validated
Jan 11, 2019 · I am working on anomaly detection using an autoencoder neural network with $1$ hidden layer. This is an unsupervised setting, as I do not have previous examples of …
autoencoders - Learning prior p (z) in VAEs - Cross Validated
Jan 16, 2021 · The paper Ma et al. 2018 states the following statement about a VAE model: Usually, the prior $p_{\\theta}(z)$ is standard normal, but we find that parameterizing it ...
autoencoders - Should I be using batchnorm and/or dropout in a …
May 1, 2022 · I am trying to design some generative NN models on datasets of RGB images and was debating on whether I should be using dropout and/or batch norm. Here are my thoughts …