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Data-driven combined state and parameter reduction for inverse problems

Overview of attention for article published in Advances in Computational Mathematics, July 2015
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1 X user

Citations

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12 Mendeley
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Title
Data-driven combined state and parameter reduction for inverse problems
Published in
Advances in Computational Mathematics, July 2015
DOI 10.1007/s10444-015-9420-5
Authors

Christian Himpe, Mario Ohlberger

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 33%
Other 1 8%
Professor 1 8%
Student > Master 1 8%
Researcher 1 8%
Other 1 8%
Unknown 3 25%
Readers by discipline Count As %
Mathematics 3 25%
Engineering 3 25%
Agricultural and Biological Sciences 1 8%
Computer Science 1 8%
Unknown 4 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 January 2014.
All research outputs
#20,216,580
of 22,739,983 outputs
Outputs from Advances in Computational Mathematics
#75
of 104 outputs
Outputs of similar age
#219,353
of 262,525 outputs
Outputs of similar age from Advances in Computational Mathematics
#1
of 1 outputs
Altmetric has tracked 22,739,983 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 104 research outputs from this source. They receive a mean Attention Score of 1.9. This one is in the 1st percentile – i.e., 1% 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 262,525 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 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