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Continualization of Probabilistic Programs With Correction
Probabilistic Programming offers a concise way to represent stochastic models and perform automated statistical inference. However, many real-world models have discrete or hybrid discrete-continuous distributions, for which existing tools may suffer non-trivial limitations. Inference and parameter e...
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| Pubblicato in: | Programming Languages and Systems |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7702239/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-44914-8_14 |
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