Many problems in machine learning and statistics involve nested expectations and thus do
not permit conventional Monte Carlo (MC) estimation. For such problems, one must nest …

Imagine a world where computational simulations can be inverted as easily as running them
forwards, where data can be used to refine models automatically, and where the only …

We formalize the notion of nesting probabilistic programming queries and investigate the
resulting statistical implications. We demonstrate that while query nesting allows the …

We present a formalization of nested Monte Carlo (NMC) estimation, whereby terms in an
outer estimator are themselves the output of separate, nested, Monte Carlo (MC) estimators …