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X Demographics
Attention Score in Context
| Title |
Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation Using Compact Implicit Layers
|
|---|---|
| Published in |
SIAM Journal on Scientific Computing, June 2024
|
| DOI | 10.1137/23m1583302 |
| Authors |
Bar Lerer, Ido Ben-Yair, Eran Treister |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
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 07 March 2024.
All research outputs
#17,247,684
of 26,109,760 outputs
Outputs from SIAM Journal on Scientific Computing
#512
of 1,245 outputs
Outputs of similar age
#79,619
of 169,917 outputs
Outputs of similar age from SIAM Journal on Scientific Computing
#1
of 2 outputs
Altmetric has tracked 26,109,760 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,245 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 56% 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 169,917 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 50% 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