The data shown below were collected from the profiles of 887 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
Title |
Deep Neural Networks and Tabular Data: A Survey
|
---|---|
Published in |
IEEE Transactions on Neural Networks and Learning Systems, June 2024
|
DOI | 10.1109/tnnls.2022.3229161 |
Pubmed ID | |
Authors |
Vadim Borisov, Tobias Leemann, Kathrin Seßler, Johannes Haug, Martin Pawelczyk, Gjergji Kasneci |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 77 | 9% |
India | 37 | 4% |
Japan | 22 | 2% |
Brazil | 18 | 2% |
Spain | 14 | 2% |
Germany | 13 | 1% |
Canada | 12 | 1% |
United Kingdom | 10 | 1% |
France | 8 | <1% |
Other | 128 | 14% |
Unknown | 548 | 62% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 685 | 77% |
Scientists | 192 | 22% |
Practitioners (doctors, other healthcare professionals) | 6 | <1% |
Science communicators (journalists, bloggers, editors) | 3 | <1% |
Unknown | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 560 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 560 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 74 | 13% |
Researcher | 68 | 12% |
Student > Master | 52 | 9% |
Student > Bachelor | 31 | 6% |
Other | 25 | 4% |
Other | 62 | 11% |
Unknown | 248 | 44% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 139 | 25% |
Engineering | 55 | 10% |
Economics, Econometrics and Finance | 12 | 2% |
Unspecified | 12 | 2% |
Mathematics | 10 | 2% |
Other | 71 | 13% |
Unknown | 261 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 569. 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 10 June 2024.
All research outputs
#44,654
of 26,567,854 outputs
Outputs from IEEE Transactions on Neural Networks and Learning Systems
#1
of 3,454 outputs
Outputs of similar age
#648
of 322,053 outputs
Outputs of similar age from IEEE Transactions on Neural Networks and Learning Systems
#1
of 50 outputs
Altmetric has tracked 26,567,854 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,454 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 99% 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 322,053 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.