Title: Tutorial on probabilistic programming languages
Authors: Kimmig, Angelika
Issue Date: 2015
Publisher: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
Host Document: Challenges and Trends in Probabilistic Programming (Dagstuhl Seminar 15181) pages:134-134
Series Title: Dagstuhl Reports
Conference: Dagstuhl Seminar edition:15181 location:Dagstuhl, Germany date:27-30 April 2015
Abstract: Probabilistic programming languages combine programming languages with probabilistic primitives as well as general purpose probabilistic inference techniques. They thus facilitate constructing and querying complex probabilistic models. This tutorial provides a gentle introduction to the field through a number of core probabilistic programming concepts. It focuses on probabilistic logic programming (PLP), but also connects to related areas such as statistical relational learning and probabilistic databases. The tutorial illustrates the concepts through examples, discusses the key ideas underlying inference in PLP, and touches upon parameter learning, language extensions, and applications in areas such as bioinformatics, object tracking and information processing.
An interactive tutorial can be found at
Publication status: published
KU Leuven publication type: IMa
Appears in Collections:Informatics Section

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