[40] Neural Discrete Representation Learning

TL;DR

task : image generation
problem : posterior collapse in generation model
idea : discrete latent variable (idea from vector quantization)
architecture : #45 with codebook(find nearest embedding vector) -> need copying gradient!
objective : reconstruction error + embedding loss w.r.t. reconstruction error + commitment loss(to train embedding + encoder in similar pace)
baseline : VAE, VIMCO
data : CIFAR10
result : qualitatively good!
contribution : VAE with discrete latent vector