You can generate a posterior distribution for any overdetermined problem. Basically, any scientific problem, as they must infer models inputs (parameteric or no

You can generate a posterior distribution for any overdetermined problem. Basically, any scientific problem, as they must infer models inputs (parameteric or non-parametric) from observed model outputs (data). Determinism is a nice illusion that quickly breaks down on real data. Scientific problems are non-unique and noise or inadequate models cause data and model to not mesh with one another. Deterministic answers have the property of being precisely wrong as opposed to mostly correct.