Improving Normalizing Flows with Padding-Dimensional Noise

PaddingFlow is a novel dequantization method that improves normalizing flows by addressing issues related to manifold and discrete data distributions. The approach of PaddingFlow involves adding padding-dimensional noise to generate unbiased estimations of the data.