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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Vydané v:	Programming Languages and Systems Ročník 12648; s. 404
Hlavní autori:	Lunden, Daniel, Borgström, Johannes, Broman, David
Médium:	Kapitola Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	Switzerland Springer International Publishing AG 01.01.2021
Edícia:	Lecture Notes in Computer Science
Predmet:	Functional Programming Measure Theory Operational Semantics Probabilistic Programming Sequential Monte Carlo
ISBN:	3030720187, 9783030720186, 3030720195, 9783030720193
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