Composing inference algorithms as program transformations

Probabilistic inference procedures are usually coded painstakingly from scratch, for each target model and each inference algorithm. We reduce this effort by generating inference procedures from models automatically. We make this code generation modular by decomposing inference algorithms into reusa...

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Bibliographische Detailangaben

Hauptverfasser:	Zinkov, Robert, Shan, Chung-chieh
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Statistics - Computation Statistics - Machine Learning Statistics - Methodology
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