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Programming Languages and Systems

Overview of attention for book
Attention for Chapter 2: Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
5 X users

Readers on

mendeley
2 Mendeley
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Chapter title
Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference
Chapter number 2
Book title
Programming Languages and Systems
Published in
arXiv, March 2022
DOI 10.1007/978-3-030-99336-8_2
Book ISBNs
978-3-03-099335-1, 978-3-03-099336-8
Authors

Daniel Lundén, Joey Öhman, Jan Kudlicka, Viktor Senderov, Fredrik Ronquist, David Broman, Lundén, Daniel, Öhman, Joey, Kudlicka, Jan, Senderov, Viktor, Ronquist, Fredrik, Broman, David

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 50%
Unknown 1 50%
Readers by discipline Count As %
Engineering 1 50%
Unknown 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 May 2023.
All research outputs
#7,324,574
of 24,323,943 outputs
Outputs from arXiv
#153,674
of 1,032,884 outputs
Outputs of similar age
#142,163
of 432,117 outputs
Outputs of similar age from arXiv
#5,589
of 35,883 outputs
Altmetric has tracked 24,323,943 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,032,884 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 432,117 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 35,883 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.