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Optimization of mesh hierarchies in multilevel Monte Carlo samplers

Overview of attention for article published in Stochastics and Partial Differential Equations: Analysis and Computations, June 2015
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Mentioned by

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3 X users

Citations

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35 Dimensions

Readers on

mendeley
25 Mendeley
Title
Optimization of mesh hierarchies in multilevel Monte Carlo samplers
Published in
Stochastics and Partial Differential Equations: Analysis and Computations, June 2015
DOI 10.1007/s40072-015-0049-7
Authors

Abdul-Lateef Haji-Ali, Fabio Nobile, Erik von Schwerin, Raúl Tempone

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 2 8%
United States 1 4%
Unknown 22 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 44%
Researcher 5 20%
Professor > Associate Professor 2 8%
Student > Master 2 8%
Professor 1 4%
Other 0 0%
Unknown 4 16%
Readers by discipline Count As %
Mathematics 11 44%
Engineering 6 24%
Agricultural and Biological Sciences 1 4%
Computer Science 1 4%
Unknown 6 24%
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 12 March 2014.
All research outputs
#16,821,304
of 25,515,042 outputs
Outputs from Stochastics and Partial Differential Equations: Analysis and Computations
#7
of 73 outputs
Outputs of similar age
#159,912
of 282,280 outputs
Outputs of similar age from Stochastics and Partial Differential Equations: Analysis and Computations
#1
of 3 outputs
Altmetric has tracked 25,515,042 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 73 research outputs from this source. They receive a mean Attention Score of 1.0. This one has done well, scoring higher than 84% 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 282,280 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
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