Essays on probability, dependence, and modeling risk where standard methods break. Looking for tutorials and technical notes? Those live in Notes.
A position statement on probaverse: building the distribution you need should be as easy as describing it.
Supervised learning almost always predicts the mean. But the question that usually matters is the whole conditional distribution — what's possible, not just what's expected.
