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Better Languages for Statistics

1st October 2020 to 30th September 2025

BLAST is an ERC funded project (consolidator grant) that will run from Oct 2020 until Sept 2025.

Probabilistic programming is a powerful method for Bayesian statistical modelling, particularly where the sample space is complex or unbounded (non-parametric). This is because the statistical model can be described clearly in a way that is precise but separate from inference algorithms. It accommodates complex models in such a way that outcomes are still explainable. The objective of the proposed research is to develop a semantic foundation for probabilistic programming that properly explains the non-parametric aspects, particularly the symmetries that arise there. There are three ultimate goals:

  • to propose new probabilistic programming languages: better languages for statistics;
  • to devise new general inference methods for probabilistic programs;
  • to build new foundations for probability.

The method is to build on advances on exploiting symmetries in traditional programming language semantics, by combining this with recent successes in formal semantics and verification for probabilistic programming.


Principal Investigator


Sean Moss
Senior Research Associate
Paolo Perrone
Research Associate
Ned Summers
Doctoral Student

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