  Event generation for the LHC can be supplemented by generative adversarial
networks, which generate physical events and avoid highly inefficient event
unweighting. For top pair production we show how such a network describes
intermediate on-shell particles, phase space boundaries, and tails of
distributions. In particular, we introduce the maximum mean discrepancy to
resolve sharp local features. It can be extended in a straightforward manner to
include for instance off-shell contributions, higher orders, or approximate
detector effects.
