DagRep.13.6.1.pdf
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Scalable Analysis of Probabilistic Models and Programs (Dagstuhl Seminar 23241)
Authors and all authors of the abstracts in this report
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Dagstuhl Reports, Volume 13, Issue 6
Volume: Dagstuhl Reports, Volume 13
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2024-02-01
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Sebastian Junges, Joost-Pieter Katoen, Scott Sanner, Guy Van den Broeck, and Bahare Salmani. Scalable Analysis of Probabilistic Models and Programs (Dagstuhl Seminar 23241). In Dagstuhl Reports, Volume 13, Issue 6, pp. 1-21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/DagRep.13.6.1
https://doi.org/10.4230/DagRep.13.6.1
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23241 "Scalable Analysis of Probabilistic Models and Programs". The seminar brought together researchers from probabilistic graphical models, verification of probabilistic programming languages, and probabilistic planning. The communities bring vastly different perspectives on the methods and goals of inference under uncertainty. In this seminar, we worked towards a common understanding of how the different angles yield subtle differences in the problem statements and how the different methods provide different strengths and weaknesses. The report describes the different areas, the activities during the seminar including hot topics that were vividly discussed, and an overview of the technical talks.
Subject Classification
ACM Subject Classification
- Computing methodologies → Planning under uncertainty
- Computing methodologies → Probabilistic reasoning
- Theory of computation → Automated reasoning
Keywords
- model counting
- probabilistic inference
- probabilistic model checking
- probabilistic planning
- probabilistic programs
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