Variational Autoencoders for Parameterized Minimum Mean Squared Error Estimation
The authors propose a variational autoencoder (VAE)-based framework for parameterizing a conditional linear minimum mean squared error (MMSE) estimator, which can approximate the MMSE estimator by utilizing the VAE as a generative prior for the estimation problem.
