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Gated Recurrent Units Viewed Through the Lens of Continuous Time Dynamical Systems

Overview of attention for article published in Frontiers in Computational Neuroscience, July 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
16 X users
reddit
1 Redditor

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
31 Mendeley
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Title
Gated Recurrent Units Viewed Through the Lens of Continuous Time Dynamical Systems
Published in
Frontiers in Computational Neuroscience, July 2021
DOI 10.3389/fncom.2021.678158
Pubmed ID
Authors

Ian D. Jordan, Piotr Aleksander Sokół, Il Memming Park

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 23%
Student > Bachelor 5 16%
Student > Master 4 13%
Student > Ph. D. Student 2 6%
Professor 1 3%
Other 2 6%
Unknown 10 32%
Readers by discipline Count As %
Engineering 6 19%
Computer Science 5 16%
Neuroscience 3 10%
Mathematics 2 6%
Unspecified 2 6%
Other 3 10%
Unknown 10 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 02 March 2024.
All research outputs
#5,291,874
of 25,563,770 outputs
Outputs from Frontiers in Computational Neuroscience
#229
of 1,469 outputs
Outputs of similar age
#114,076
of 445,704 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#4
of 27 outputs
Altmetric has tracked 25,563,770 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,469 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. 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 445,704 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 74% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.