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Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference
Lundén, Daniel
ORCID iD:
0000-0003-3127-5640
Öhman, Joey
KTH Royal Institute of Technology.
ORCID iD:
0000-0001-6342-268X
Kudlicka, Jan
BI Norwegian Business School.
ORCID iD:
0000-0003-3806-4950
Senderov, Viktor
Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
(Fredrik Ronquists grupp)
ORCID iD:
0000-0003-3340-5963
Ronquist, Fredrik
Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
(Fredrik Ronquists grupp)
ORCID iD:
0000-0002-3929-251X
Broman, David
KTH Royal Institute of Technology.
ORCID iD:
0000-0001-8457-4105
Show others and affiliations
2022 (English)
In:
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 13240, p. 29-56
Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2022. Vol. 13240, p. 29-56
National Category
Bioinformatics and Systems Biology
Research subject
Diversity of life
Identifiers
URN:
urn:nbn:se:nrm:diva-5148
DOI:
10.1007/978-3-030-99336-8_2
OAI: oai:DiVA.org:nrm-5148
DiVA, id:
diva2:1723679
Conference
ESOP 2022
Funder
Swedish Research Council, 2018-04620
EU, Horizon 2020, 898120
Available from:
2023-01-03
Created:
2023-01-03
Last updated:
2023-01-04
Bibliographically approved
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Lundén, Daniel
Öhman, Joey
Kudlicka, Jan
Senderov, Viktor
Ronquist, Fredrik
Broman, David
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Department of Bioinformatics and Genetics
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Lecture Notes in Computer Science
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Bioinformatics and Systems Biology
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modern-language-association-8th-edition
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ieee
modern-language-association-8th-edition
vancouver
Other style
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en-GB
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nn-NB
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