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Grammars for Games: A Gradient-Based, Game-Theoretic Framework for Optimization in Deep Learning

Overview of attention for article published in Frontiers in Robotics and AI, January 2016
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  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 X users

Citations

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4 Dimensions

Readers on

mendeley
30 Mendeley
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Title
Grammars for Games: A Gradient-Based, Game-Theoretic Framework for Optimization in Deep Learning
Published in
Frontiers in Robotics and AI, January 2016
DOI 10.3389/frobt.2015.00039
Authors

David Balduzzi

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 7%
United Kingdom 1 3%
New Zealand 1 3%
United States 1 3%
Unknown 25 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Researcher 7 23%
Student > Bachelor 5 17%
Other 3 10%
Student > Master 3 10%
Other 4 13%
Unknown 1 3%
Readers by discipline Count As %
Computer Science 21 70%
Engineering 3 10%
Psychology 2 7%
Physics and Astronomy 2 7%
Agricultural and Biological Sciences 1 3%
Other 0 0%
Unknown 1 3%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 January 2016.
All research outputs
#13,762,231
of 23,335,153 outputs
Outputs from Frontiers in Robotics and AI
#709
of 1,541 outputs
Outputs of similar age
#192,671
of 396,188 outputs
Outputs of similar age from Frontiers in Robotics and AI
#8
of 11 outputs
Altmetric has tracked 23,335,153 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,541 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has gotten more attention than average, scoring higher than 51% 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 396,188 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.