For new, easier probabilistic programming languages
Today’s scientists benefit from the accessibility of various databases. But analysis requires new methods in probabilities reasoning and more precise tools. Probabilistic programming learns from methods of programming languages to apply them in designing and using a special programming language for statistical models. It’s used in Bayesian statistics modelling, mainly for a complex, non-parametric sample space, in which the statistical model can be explained in a precise way, but separately from inference algorithms mostly limited in scope. The EU-funded BLaSt project aims at research that will allow creating a semantic base for new probabilistic programming languages and, especially, for a programming language explaining precisely the non-parametric aspects in the symmetries that emerge.
Fields of science
Funding SchemeERC-COG - Consolidator Grant
OX1 2JD Oxford
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