Correctness of Sequential Monte Carlo Inference for Probabilistic Programming Languages

Probabilistic programming is an approach to reasoning under uncertainty by encoding inference problems as programs. In order to solve these inference problems, probabilistic programming languages (PPLs) employ different inference algorithms, such as sequential Monte Carlo (SMC), Markov chain Monte C...

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Veröffentlicht in:	Programming Languages and Systems Jg. 12648; S. 404
Hauptverfasser:	Lunden, Daniel, Borgström, Johannes, Broman, David
Format:	Buchkapitel Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	Switzerland Springer International Publishing AG 01.01.2021
Schriftenreihe:	Lecture Notes in Computer Science
Schlagworte:	Functional Programming Measure Theory Operational Semantics Probabilistic Programming Sequential Monte Carlo
ISBN:	3030720187, 9783030720186, 3030720195, 9783030720193
Online-Zugang:	Volltext
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