↓ Skip to main content

In situ training of feed-forward and recurrent convolutional memristor networks

Overview of attention for article published in Nature Machine Intelligence, September 2019
Altmetric Badge

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 (75th percentile)

Mentioned by

twitter
2 X users
patent
2 patents

Citations

dimensions_citation
209 Dimensions

Readers on

mendeley
118 Mendeley
Title
In situ training of feed-forward and recurrent convolutional memristor networks
Published in
Nature Machine Intelligence, September 2019
DOI 10.1038/s42256-019-0089-1
Authors

Zhongrui Wang, Can Li, Peng Lin, Mingyi Rao, Yongyang Nie, Wenhao Song, Qinru Qiu, Yunning Li, Peng Yan, John Paul Strachan, Ning Ge, Nathan McDonald, Qing Wu, Miao Hu, Huaqiang Wu, R. Stanley Williams, Qiangfei Xia, J. Joshua Yang

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 118 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 27%
Student > Master 15 13%
Student > Bachelor 10 8%
Researcher 10 8%
Student > Doctoral Student 5 4%
Other 7 6%
Unknown 39 33%
Readers by discipline Count As %
Engineering 37 31%
Materials Science 9 8%
Computer Science 8 7%
Physics and Astronomy 8 7%
Chemical Engineering 2 2%
Other 4 3%
Unknown 50 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 12 September 2023.
All research outputs
#4,550,008
of 24,453,338 outputs
Outputs from Nature Machine Intelligence
#490
of 667 outputs
Outputs of similar age
#84,445
of 345,856 outputs
Outputs of similar age from Nature Machine Intelligence
#21
of 27 outputs
Altmetric has tracked 24,453,338 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 667 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 65.3. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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 345,856 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% 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 is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.