Data Science, Causality, Statistics, Advertising, Python.
density estimates does not get around this problem. The weighting sampler, for instance, uses kernel density estimation for continuous causal states. In the tails of empirical distributions, this approach can over-estimate propensities, and so weights that should be very large might end much