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Deep learning’s shallow gains: a comparative evaluation of algorithms for automatic music generation

Overview of attention for article published in Machine Learning, March 2023
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#8 of 1,051)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
6 news outlets
blogs
1 blog
twitter
8 X users

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
34 Mendeley
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Title
Deep learning’s shallow gains: a comparative evaluation of algorithms for automatic music generation
Published in
Machine Learning, March 2023
DOI 10.1007/s10994-023-06309-w
Authors

Zongyu Yin, Federico Reuben, Susan Stepney, Tom Collins

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 12%
Student > Master 3 9%
Student > Bachelor 3 9%
Unspecified 2 6%
Student > Postgraduate 2 6%
Other 6 18%
Unknown 14 41%
Readers by discipline Count As %
Computer Science 10 29%
Engineering 4 12%
Arts and Humanities 2 6%
Unspecified 2 6%
Mathematics 1 3%
Other 2 6%
Unknown 13 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 56. 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 11 August 2023.
All research outputs
#704,808
of 24,248,886 outputs
Outputs from Machine Learning
#8
of 1,051 outputs
Outputs of similar age
#15,179
of 405,318 outputs
Outputs of similar age from Machine Learning
#1
of 35 outputs
Altmetric has tracked 24,248,886 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,051 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 99% 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 405,318 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 96% of its contemporaries.
We're also able to compare this research output to 35 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 99% of its contemporaries.