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Better Languages for Statistics: foundations for non-parametric probabilistic programming

Project description

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.

Call for proposal

ERC-2019-COG
See other projects for this call

Funding Scheme

ERC-COG - Consolidator Grant

Host institution

THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Address
Wellington Square University Offices
OX1 2JD Oxford
United Kingdom
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 1 931 178

Beneficiaries (1)

THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
United Kingdom
EU contribution
€ 1 931 178
Address
Wellington Square University Offices
OX1 2JD Oxford
Activity type
Higher or Secondary Education Establishments