How to create a variational autoencoder with Keras?
In a different blog post, we studied the concept of a Variational Autoencoder (or VAE) in detail. The models, which...
Tag: autoencoder
How to visualize the encoded state of an autoencoder with Keras?
Autoencoders are special types of neural networks which learn to convert inputs into lower-dimensional form, after which they convert it...
What is a Variational Autoencoder (VAE)?
Suppose that you have an image of a man with a moustache and one of a man without one. You...
How to use Kullback-Leibler divergence (KL divergence) with Keras?
When you train a supervised machine learning model, you feed forward data, generating predictions on the fly. The comparison of...
Building an Image Denoiser with a Keras autoencoder neural network
Images can be noisy, and you likely want to have this noise removed. Traditional noise removal filters can be used...
Creating a Signal Noise Removal Autoencoder with Keras
Pure signals only exist in theory. That is, when you’re doing signal processing related activities, it’s very likely that you’ll...
UpSampling2D: how to use upsampling with Keras?
The Convolutional layers section of the Keras API contains the so-called UpSampling2D layer. But what does it do? And how...
Conv2DTranspose: using 2D transposed convolutions with Keras
Transposed convolutions – we looked at them in theory in a previous blog post, but how can they be applied?...
