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Daniel Lundén
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Delayed sampling and automatic Rao-Blackwellization of probabilistic programs
L Murray, D Lundén, J Kudlicka, D Broman, T Schön
International Conference on Artificial Intelligence and Statistics, 1037-1046, 2018
592018
Universal probabilistic programming offers a powerful approach to statistical phylogenetics
F Ronquist, J Kudlicka, V Senderov, J Borgström, N Lartillot, D Lundén, ...
Communications biology 4 (1), 244, 2021
352021
Correctness of Sequential Monte Carlo Inference for Probabilistic Programming Languages.
D Lundén, J Borgström, D Broman
ESOP, 404-431, 2021
132021
Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference.
D Lundén, J Öhman, J Kudlicka, V Senderov, F Ronquist, D Broman
ESOP, 29-56, 2022
92022
Delayed sampling in the probabilistic programming language Anglican
D Lundén
82017
Automatic alignment of Sequential Monte Carlo inference in higher-order probabilistic programs
D Lundén, D Broman, F Ronquist, LM Murray
arXiv preprint arXiv:1812.07439, 2018
52018
Probabilistic programming: a powerful new approach to statistical phylogenetics
F Ronquist, J Kudlicka, V Senderov, J Borgström, N Lartillot, D Lundén, ...
32020
Automatic Alignment in Higher-Order Probabilistic Programming Languages.
D Lundén, G Çaylak, F Ronquist, D Broman
ESOP, 535-563, 2023
22023
Combining static and dynamic optimizations using closed-form solutions
D Lundén, D Broman, LM Murray
Proceedings of the Workshop on Probabilistic Programming Semantics (PPS) 3, 2018
12018
Factoring integers with parallel SAT solvers
D Lundén, E Forsblom
12015
Suspension Analysis and Selective Continuation-Passing Style for Higher-Order Probabilistic Programming Languages
D Lundén, L Hummelgren, J Kudlicka, O Eriksson, D Broman
arXiv preprint arXiv:2302.13051, 2023
2023
TreePPL: A Universal Probabilistic Programming Language for Phylogenetics
VE Senderov, J Kudlicka, D Lunden, V Palmkvist, MP Braga, E Granqvist, ...
bioRxiv, 2023.10. 10.561673, 2023
2023
Correct and Efficient Monte Carlo Inference for Universal Probabilistic Programming Languages
D Lundén
KTH Royal Institute of Technology, 2023
2023
Publisher Correction: Universal probabilistic programming offers a powerful approach to statistical phylogenetics
F Ronquist, J Kudlicka, V Senderov, J Borgström, N Lartillot, D Lundén, ...
Communications Biology 4, 2021
2021
Compilation of Universal Probabilistic Programs to GPGPUs
D Lundén, J Öhman, D Broman
Automatic Discovery of Static Structures in Probabilistic Programs
D Lundén, D Broman, F Ronquist, LM Murray
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Articles 1–16