Machine Learning, Generative Model, Bayesian Machine Learning.
you have overlap, but in cases of non-overlapping distributions, it just becomes infinite. A good mental image of this is the sigmoid function: it’s domain is between zero and one, and so moving farther away once you’ve already saturated in either the 0 or 1 direction leads to gradients flattening