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.

@article{JungesDagstuhl24,
  title     = {Scalable Analysis of Probabilistic Models and Programs (Dagstuhl Seminar 23241)},
  author    = {Junges, Sebastian and Katoen, Joost-Pieter and Sanner, Scott and Van den Broeck, Guy and Salmani, Bahare},
  journal   = {Dagstuhl Reports},
  volume    = {13},
  number    = {6},
  pages     = {1--21},
  doi       = {10.4230/DagRep.13.6.1},
  url       = "https://starai.cs.ucla.edu/papers/JungesDagstuhl24.pdf",
  month     = 2,
  year      = {2024},
  keywords  = {techreport}
}