one that everyone does so far is to sample uniformly from the training data and also to sample uniformly from the z space but you could imagine the importance sampling could give us big improvements in particular most of the points that we train the generator on are wasted because we're usually going to sample from points that are doing pretty well and what we'd really like to do is find points that are doing very badly or maybe points that lie on the boundary between two modes in order to adjust those boundaries so you could imagine