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Learning Without Feedback: Fixed Random Learning Signals Allow for Feedforward Training of Deep Neural Networks

Overview of attention for article published in Frontiers in Neuroscience, February 2021
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
1 news outlet
twitter
34 X users
reddit
1 Redditor

Citations

dimensions_citation
51 Dimensions

Readers on

mendeley
62 Mendeley
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Title
Learning Without Feedback: Fixed Random Learning Signals Allow for Feedforward Training of Deep Neural Networks
Published in
Frontiers in Neuroscience, February 2021
DOI 10.3389/fnins.2021.629892
Pubmed ID
Authors

Charlotte Frenkel, Martin Lefebvre, David Bol

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 34 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 16%
Student > Master 10 16%
Student > Bachelor 5 8%
Researcher 4 6%
Student > Doctoral Student 2 3%
Other 8 13%
Unknown 23 37%
Readers by discipline Count As %
Computer Science 17 27%
Engineering 9 15%
Neuroscience 3 5%
Agricultural and Biological Sciences 2 3%
Unspecified 2 3%
Other 5 8%
Unknown 24 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. 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 06 December 2022.
All research outputs
#1,306,503
of 25,492,047 outputs
Outputs from Frontiers in Neuroscience
#580
of 11,584 outputs
Outputs of similar age
#37,926
of 537,971 outputs
Outputs of similar age from Frontiers in Neuroscience
#28
of 404 outputs
Altmetric has tracked 25,492,047 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,584 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done particularly well, scoring higher than 95% 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 537,971 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 92% of its contemporaries.
We're also able to compare this research output to 404 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.