Event generation with neural networks has seen
significant progress recently. The big open question is
still how such new methods will accelerate LHC simulations
to the level required by upcoming LHC runs. We target a
known bottleneck of standard simulations and show how their
unweighting procedure can be improved by generative
networks. This can, potentially, lead to a very significant
gain in simulation speed.
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