Declarative Probabilistic Programming with Datalog

Abstract

Probabilistic programming languages are used for developing statistical models. They typically consist of two components: a specification of a stochastic process (the prior) and a specification of observations that restrict the probability space to a conditional subspace (the posterior). Use cases of such formalisms include the development of algorithms in machine learning and artificial intelligence.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 27, 2017
Source ID
10.1145/3132700

Entities

People

  • Balder Ten Cate
  • Benny Kimelfeld
  • Dan Olteanu
  • Vince Bárány
  • Zografoula Vagena

Organizations

  • Defense Advanced Research Projects Agency
  • Engineering and Physical Sciences Research Council
  • Israel Science Foundation
  • Technion – Israel Institute of Technology
  • University of Oxford

Tags

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Linguistics

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space