According the the paper, VQ-VAE goes through two stage training. First to train the encoder and the vector quantization and then train an auto-regressive model
I am trying to train a lstm autoencoder to convert the input space to a latent space and then visualize it, and I hope to find some interesting patterns in the
I'm working on a torch-based library for building autoencoders with tabular datasets. One big feature is learning embeddings for categorical features. In pra