Bachelor's thesis on generative probabilistic programming (in Russian language, June 2014)

TL;DR

This Bachelor's thesis explores probabilistic programming, reviewing existing languages and presenting initial experiments on automatic program induction, contributing to the understanding of this emerging AI field.

Contribution

It provides an overview of probabilistic programming languages and reports early experimental results on automatic induction of probabilistic programs.

Findings

Reviewed existing probabilistic programming languages: Church, Venture, Anglican

Conducted initial experiments on automatic induction of probabilistic programs

Contributed to foundational understanding of probabilistic programming applications

Abstract

This Bachelor's thesis, written in Russian, is devoted to a relatively new direction in the field of machine learning and artificial intelligence, namely probabilistic programming. The thesis gives a brief overview to the already existing probabilistic programming languages: Church, Venture, and Anglican. It also describes the results of the first experiments on the automatic induction of probabilistic programs. The thesis was submitted, in June 2014, in partial fulfilment of the requirements for the degree of Bachelor of Science in Mathematics in the Department of Mathematics and Computer Science, Siberian Federal University, Krasnoyarsk, Russia. The work, which is described in this thesis, has been performing in 2012-2014 in the Massachusetts Institute of Technology and in the University of Oxford by the colleagues of the author and by himself.