13 citations · 24 across the 5 of their papers we have counts for
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cs.PL2023★ 2 cited
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…
cs.PL2021★ 13 cited
Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference
Daniel Lundén, Joey Öhman, Jan Kudlicka +3
Probabilistic programming languages (PPLs) allow users to encode arbitrary inference problems, and PPL implementations provide general-purpose automatic inference for these problem…