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Attention Score in Context
Title |
Correction to Universal Approximation Power of Deep Residual Neural Networks Through the Lens of Control
|
---|---|
Published in |
IEEE Transactions on Automatic Control, April 2024
|
DOI | 10.1109/tac.2024.3390099 |
Authors |
Paulo Tabuada, Bahman Gharesifard |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 April 2024.
All research outputs
#8,693,662
of 25,757,133 outputs
Outputs from IEEE Transactions on Automatic Control
#202
of 1,547 outputs
Outputs of similar age
#51,585
of 161,478 outputs
Outputs of similar age from IEEE Transactions on Automatic Control
#1
of 2 outputs
Altmetric has tracked 25,757,133 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,547 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 35th percentile – i.e., 35% 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 161,478 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 66% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them