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An Introduction to Variational Methods for Graphical Models

Overview of attention for article published in Machine Learning, November 1999
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
1 X user
patent
13 patents
wikipedia
4 Wikipedia pages

Citations

dimensions_citation
1853 Dimensions

Readers on

mendeley
2193 Mendeley
citeulike
26 CiteULike
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Title
An Introduction to Variational Methods for Graphical Models
Published in
Machine Learning, November 1999
DOI 10.1023/a:1007665907178
Authors

Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 2,193 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 84 4%
United Kingdom 24 1%
China 18 <1%
France 13 <1%
Spain 12 <1%
Switzerland 10 <1%
Germany 9 <1%
Canada 6 <1%
Brazil 5 <1%
Other 58 3%
Unknown 1954 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 733 33%
Researcher 387 18%
Student > Master 308 14%
Student > Bachelor 120 5%
Professor > Associate Professor 93 4%
Other 317 14%
Unknown 235 11%
Readers by discipline Count As %
Computer Science 1029 47%
Engineering 296 13%
Mathematics 182 8%
Agricultural and Biological Sciences 97 4%
Physics and Astronomy 45 2%
Other 258 12%
Unknown 286 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 13 February 2024.
All research outputs
#3,722,734
of 25,837,817 outputs
Outputs from Machine Learning
#98
of 1,266 outputs
Outputs of similar age
#3,031
of 37,616 outputs
Outputs of similar age from Machine Learning
#1
of 5 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,266 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 91% 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 37,616 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them