What is the difference between convolutional neural networks ...
I can't tell you much about RBMs, but autoencoders and CNNs are two different kinds of things. An autoencoder is a neural network that is trained in an unsupervised fashion. The goal of an …
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
Mar 23, 2019 · 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 …
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 …
Why binary crossentropy can be used as the loss function in …
Instead, KL-divergence is usually used as the loss function in this specific type of autoencoders. If you have any example of autoencoder trained using MSE and BCE loss and there is a …
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 …