Several applications in communication, control, and learning require approximating target distributions to within small informational divergence. The additional requirement of invertibility usually leads using encoders that are one-to-one mappings, also known as distribution matchers. However, even the best have divergences grow logarithmically with block length. To overcome this limitation, an...