s ⇠ is not used at test time, but only as part of our training objective.
vIB goes beyond mere dimensionality reduction to a fixed lower dimensionality, since it also avoids unnecessary use of the dimensions that are available in the compressed representation, blurring unneeded capacity via randomness.