λPSI: exact inference for higher-order probabilistic programs
Timon Gehr, Samuel Steffen, Martin Vechev
Abstract
We present λPSI, the first probabilistic programming language and system that supports higher-order exact inference for probabilistic programs with first-class functions, nested inference and discrete, continuous and mixed random variables. λPSI’s solver is based on symbolic reasoning and computes the exact distribution represented by a program.
Topics & Concepts
Probabilistic logicInferenceComputer scienceVariable eliminationClass (philosophy)Theoretical computer scienceSolverProgramming languageAlgorithmArtificial intelligenceBayesian Modeling and Causal InferenceMachine Learning and AlgorithmsFormal Methods in Verification