Mark V. Culp
Impact in
- Software top 5%
- Software Reliability and Analysis Research
- Software Testing and Debugging Techniques
- Information Systems top 5%
- Software Engineering Research
Papers in
-
- Machine Learning and Data Classification 5
- Machine Learning and Algorithms 4
-
- Statistical Methods and Inference 4
- Co-authors
- George Michailidis (7 shared papers)Bojan Čukić (4 shared papers)Kjell Johnson (4 shared papers)Huihua Lu (3 shared papers)Kenneth J. Ryan (3 shared papers)Ryan J. Ice (2 shared papers)Sarah L. McLaughlin (2 shared papers)Elena N. Pugacheva (2 shared papers)
- Journals
- Journal of Computational and Graphical Statistics (3 papers)Journal of Statistical Software (2 papers)Journal of Machine Learning Research (2 papers)Information and Software Technology (1 paper)Photogrammetric Engineering & Remote Sensing (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Mark V. Culp
25 papers receiving 498 citations
Peers
Comparison fields: 5 of 101
- Software 96
- Information Systems 149
- Artificial Intelligence 147
- Computer Vision and Pattern Recognition 67
- Statistics and Probability 25
Countries citing papers authored by Mark V. Culp
This map shows the geographic impact of Mark V. Culp's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mark V. Culp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark V. Culp more than expected).
Fields of papers citing papers by Mark V. Culp
This network shows the impact of papers produced by Mark V. Culp. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mark V. Culp. The network helps show where Mark V. Culp may publish in the future.
Co-authors
The 24 scholars most cited alongside Mark V. Culp, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 81 | |
| 2 | 2006 | 70 | |
| 3 | 2012 | 52 | |
| 4 | 2013 | 38 | |
| 5 | 2016 | 35 | |
| 6 | 2008 | 32 | |
| 7 | 2011 | 26 | |
| 8 | 2013 | 24 | |
| 9 | 2012 | 23 | |
| 10 | 2013 | 21 | |
| 11 | 2011 | 21 | |
| 12 | 2014 | 16 | |
| 13 | 2009 | 15 | |
| 14 | ada: An R Package for Stochastic Boosting | 2013 | 11 |
| 15 | 2010 | 9 | |
| 16 | 2015 | 8 | |
| 17 | 2010 | 7 | |
| 18 | 2014 | 6 | |
| 19 | 2011 | 5 | |
| 20 | 2011 | 4 |
About Mark V. Culp
Mark V. Culp is a scholar working on Artificial Intelligence, Statistics and Probability, Molecular Biology, Information Systems and Computational Theory and Mathematics, having authored 25 papers that have together received 513 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (5 papers), Computational Drug Discovery Methods (4 papers), Software Engineering Research (4 papers), Statistical Methods and Inference (4 papers), Machine Learning and Algorithms (4 papers), Software Reliability and Analysis Research (3 papers), Machine Learning in Bioinformatics (2 papers) and Face and Expression Recognition (2 papers). The work is most often cited by research in Software (96 citations), Information Systems (149 citations), Artificial Intelligence (147 citations), Computer Vision and Pattern Recognition (67 citations) and Statistics and Probability (25 citations). Mark V. Culp has collaborated with scholars based in United States and Germany. Frequent co-authors include George Michailidis, Bojan Čukić, Kjell Johnson, Huihua Lu, Kenneth J. Ryan, Ryan J. Ice, Sarah L. McLaughlin, Elena N. Pugacheva, Ryan H. Livengood and Alexey V. Ivanov. Their work appears in journals such as Journal of Computational and Graphical Statistics, Journal of Statistical Software, Journal of Machine Learning Research, Information and Software Technology and Photogrammetric Engineering & Remote Sensing.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.