Guaranteed inference for probabilistic programs: a parallelisable, small-step operational approach

In the context of probabilistic programming languages, we put forward an approach to formal semantics and sampling-based inference with guarantees, centered on an action-based language equipped with a small-step operational semantics. We argue that this choice offers benefits in terms of clarity and...

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Bibliographic Details
Published in:ACM transactions on probabilistic machine learning
Main Authors: Boreale, Michele, Collodi, Luisa
Format: Journal Article
Language:English
Published: 30.09.2025
ISSN:2836-8924, 2836-8924
Online Access:Get full text
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