Probabilistic Inference by Program Transformation in Hakaru (System Description)

Abstract. We present Hakaru, a new probabilistic programming system that allows composable reuse of distributions, queries, and inference algorithms, all expressed in a single language of measures. The system implements two automatic and semantics-preserving program transformations—disintegration, which calculates conditional distributions, and simplification, which subsumes exact inference by computer algebra. We show how these features work together by describing the ideal workflow of a Hakaru user on two small problems. We highlight our composition of transformations and types in design and implementation.

• Type: Journal
• Year: 2016
• Where: FLOPS
• Authors: Praveen Narayanan, Jacques Carette, Wren Romano, Chung-chieh Shan, Robert Zinkov
• Keywords: Automated Reasoning, FLOPS 2016