Simple, denoising and variational autoencoders made in TensorFlow2.0
The code is very repetitive, for educational and learning perspective.
All experiments are made with MNIST data I have not added the evaluation scripts in the repository. That is a practice for the readers of https://medium.com/@imran.salam.24/autoencoders-guide-and-code-in-tensorflow-2-0-a4101571ce56
There are 4 files
fcn_autoencoder.py - A fully connected Autoencoder
conv_autoencoder.py - A Convolutional Autoencoder
conv_denoising_autoencoder.py - A Convolutional Denoising Autoencoder
conv_variational_autoencoder.py - A Convolutional Variational Autoencoder