Accession Number:



Inference Building Blocks

Descriptive Note:

[Technical Report, Final Report]

Corporate Author:

Indiana University

Report Date:


Pagination or Media Count:



We address the problem that probabilistic inference algorithms are difficult and tedious to implement, by expressing them in terms of a small number of building blocks, which are automatic transformations on probabilistic programs. On one hand, our curation of these building blocks reflects the way human practitioners discuss probabilistic inference with each other, so our probabilistic programming language supports modular composition of inference procedures and serves as a medium for collaboration. On the other hand, our implementation of these building blocks combines high-level mathematical reasoning with low-level computational optimization, so the speed and accuracy of the generated solvers are competitive with state-of-the-art systems.


Subject Categories:

  • Statistics and Probability

Distribution Statement:

[A, Approved For Public Release]