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arXiv · 1904.07425

The Geometry of Bayesian Programming

Ugo Dal Lago·Naohiko Hoshino
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Abstract

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.

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Ugo Dal Lago, Naohiko Hoshino. 2019-04-16. The Geometry of Bayesian Programming. https://doi.org/10.1017/s0960129521000396

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