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PyEPO: a PyTorch-based end-to-end predict-then-optimize library for linear and integer programming

Overview of attention for article published in Mathematical Programming Computation, July 2024
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Mentioned by

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1 X user

Citations

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3 Dimensions

Readers on

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39 Mendeley
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Title
PyEPO: a PyTorch-based end-to-end predict-then-optimize library for linear and integer programming
Published in
Mathematical Programming Computation, July 2024
DOI 10.1007/s12532-024-00255-x
Authors

Bo Tang, Elias B. Khalil

Timeline

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X Demographics

X Demographics

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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Ph. D. Student 6 15%
Professor 4 10%
Unspecified 2 5%
Student > Master 2 5%
Other 6 15%
Unknown 11 28%
Readers by discipline Count As %
Computer Science 9 23%
Engineering 8 21%
Business, Management and Accounting 3 8%
Decision Sciences 3 8%
Unspecified 2 5%
Other 3 8%
Unknown 11 28%
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 18 July 2024.
All research outputs
#18,017,504
of 26,356,696 outputs
Outputs from Mathematical Programming Computation
#66
of 94 outputs
Outputs of similar age
#69,412
of 142,588 outputs
Outputs of similar age from Mathematical Programming Computation
#1
of 1 outputs
Altmetric has tracked 26,356,696 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 94 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 23rd percentile – i.e., 23% 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 142,588 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% 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