  We give a geometry of interaction model for a typed lambda-calculus endowed
with operators for sampling from a continuous uniform distribution and soft
conditioning, namely a paradigmatic calculus for higher-order Bayesian
programming. The model is based on the category of measurable spaces and
partial measurable functions, and is proved adequate with respect to both a
distribution-based and a sampling based operational semantics.
