image generative models can learn the distributions of the training data and
consequently generate examples by sampling from these distributions. However,
when the training dataset is corrupted with outliers, gen
Rate-Adaptive VQ-VAE improves the adaptability and performance of Vector Quantized Variational AutoEncoders with novel codebook representation methods, achieving effective reconstruction performance across multiple rates.