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cs.PL2025
CoreDPPL: Towards a Sound Composition of Differentiation, ODE Solving, and Probabilistic Programming
Oscar Eriksson, Anders à gren Thuné, Johannes Borgström +1
In recent years, there has been extensive research on how to extend general-purpose programming language semantics with domain-specific modeling constructs. Two areas of particular…
cs.PL2024
Real-Time Probabilistic Programming
Lars Hummelgren, Matthias Becker, David Broman
Complex cyber-physical systems interact in real-time and must consider both timing and uncertainty. Developing software for such systems is expensive and difficult, especially when…
cs.PL2024
Suspension Analysis and Selective Continuation-Passing Style for Universal Probabilistic Programming Languages
Daniel Lundén, Lars Hummelgren, Jan Kudlicka +2
Universal probabilistic programming languages (PPLs) make it relatively easy to encode and automatically solve statistical inference problems. To solve inference problems, PPL impl…