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EnKSGD: A Class of Preconditioned Black Box Optimization and Inversion Algorithms

Overview of attention for article published in SIAM Journal on Scientific Computing, June 2024
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  • Above-average Attention Score compared to outputs of the same age (60th percentile)

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Title
EnKSGD: A Class of Preconditioned Black Box Optimization and Inversion Algorithms
Published in
SIAM Journal on Scientific Computing, June 2024
DOI 10.1137/23m1561142
Authors

Brian Irwin, Sebastian Reich

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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 16 January 2024.
All research outputs
#15,717,823
of 26,198,325 outputs
Outputs from SIAM Journal on Scientific Computing
#460
of 1,244 outputs
Outputs of similar age
#64,761
of 172,390 outputs
Outputs of similar age from SIAM Journal on Scientific Computing
#1
of 3 outputs
Altmetric has tracked 26,198,325 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,244 research outputs from this source. They receive a mean Attention Score of 2.2. This one has gotten more attention than average, scoring higher than 62% 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 172,390 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 60% of its contemporaries.
We're also able to compare this research output to 3 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