Auto Encoder

Autoencoders are a class of neural networks designed for unsupervised learning and representing features in a smaller space. They consist of an encoder and a decoder, intending to learn the input data's compressed representation (encoding). We leverage this architecture to generate synthetic data.

SDGnE package contains three Autoencoder models:

Balanced Autoencoder

Heavy Decoder Autoencoder

Single Encoder Autoencoder