Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs. - Lawrence M. Murray; Daniel Lundén; Jan Kudlicka; David Broman; Thomas B. Schön (AISTATS, 2018)

Automatic Alignment of Sequential Monte Carlo Inference in Higher-Order Probabilistic Programs. - Daniel Lundén; David Broman; Fredrik Ronquist; Lawrence M. Murray (CoRR, 2018)

Correctness of Sequential Monte Carlo Inference for Probabilistic Programming Languages. - Daniel Lundén; Johannes Borgström; David Broman (ESOP, 2021)

Universal Probabilistic Programming Language Compilation with Parallel Efficient Sequential Monte Carlo Inference. - Daniel Lundén; Joey Öhman; Jan Kudlicka; Viktor Senderov; Fredrik Ronquist; David Broman (CoRR, 2021)

Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference. - Daniel Lundén; Joey Öhman; Jan Kudlicka; Viktor Senderov; Fredrik Ronquist; David Broman (ESOP, 2022)

Automatic Alignment in Higher-Order Probabilistic Programming Languages. - Daniel Lundén; Gizem Çaylak; Fredrik Ronquist; David Broman (ESOP, 2023)

Suspension Analysis and Selective Continuation-Passing Style for Higher-Order Probabilistic Programming Languages. - Daniel Lundén; Lars Hummelgren; Jan Kudlicka; Oscar Eriksson; David Broman (CoRR, 2023)

Correct and Efficient Monte Carlo Inference for Universal Probabilistic Programming Languages. - Daniel Lundén (2023)

Suspension Analysis and Selective Continuation-Passing Style for Universal Probabilistic Programming Languages. - Daniel Lundén; Lars Hummelgren; Jan Kudlicka; Oscar Eriksson; David Broman (ESOP (2), 2024)

Statically and Dynamically Delayed Sampling for Typed Probabilistic Programming Languages. - Gizem Caylak; Daniel Lundén; Viktor Senderov; David Broman (SLE, 2024)