Andreas Christmann

2.9k citations
79 papers · 2.0k · h-index 22

Impact in

Papers in

Andreas Christmann

73 papers receiving 1.9k citations

Peers

Andreas Christmann
Comparison fields: 5 of 167
  • Statistics and Probability 501
  • Statistics, Probability and Uncertainty 135
  • Artificial Intelligence 514
  • Computer Vision and Pattern Recognition 307
  • Computational Mechanics 226
Replace Jun Fan with:
Jun Fan China
Yichao Wu United States
Fang Han United States
Linda Zhao United States
Aloïs Kneip Germany
Weixin Yao United States
Ricardo Fraiman Uruguay
Norbert Henze Germany
Byeong U. Park South Korea
Nicholas G. Polson United States
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Citations per field
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Citations per year

Countries citing papers authored by Andreas Christmann

Since Specialization
Citations

This map shows the geographic impact of Andreas Christmann'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 Andreas Christmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Christmann more than expected).

Fields of papers citing papers by Andreas Christmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andreas Christmann. 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 Andreas Christmann. The network helps show where Andreas Christmann may publish in the future.

Co-authors

The 25 scholars most cited alongside Andreas Christmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Andreas Christmann Line = papers co-authored together Andreas Christmann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008392
2 2005289
3 2011151
4
Cerebral ischemia detected with diffusion-weighted MR imaging after stent implantation in the carotid artery.
2002128
5 200782
6 200377
7 200059
8 200754
9
How SVMs can estimate quantiles and the median
200750
10 200145
11
Fast Learning from Non-i.i.d. Observations
200940
12 201140
13 199839
14 199438
15
Bouligand Derivatives and Robustness of Support Vector Machines for Regression
200831
16 200931
17
Universal Kernels on Non-Standard Input Spaces
201030
18 201130
19 200528
20 201527

About Andreas Christmann

Andreas Christmann is a scholar working on Statistics and Probability, Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering and Computational Mechanics, having authored 79 papers that have together received 2.0k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (32 papers), Statistical Methods and Inference (27 papers), Sparse and Compressive Sensing Techniques (11 papers), Face and Expression Recognition (10 papers), Control Systems and Identification (9 papers), Islamic Studies and History (8 papers), Advanced Statistical Process Monitoring (7 papers) and Neural Networks and Applications (6 papers). The work is most often cited by research in Statistics and Probability (501 citations), Statistics, Probability and Uncertainty (135 citations), Artificial Intelligence (514 citations), Computer Vision and Pattern Recognition (307 citations) and Computational Mechanics (226 citations). Andreas Christmann has collaborated with scholars based in Germany, Belgium and United States. Frequent co-authors include Ingo Steinwart, Stefan Van Aelst, Robert Hable, Ding‐Xuan Zhou, Arnout Van Messem, S. Hennigs, Horst J. Jaeger, Klaus Mathias, Peter J. Rousseeuw and Hans Martin Gissler. Their work appears in journals such as Computational Statistics & Data Analysis, Journal of Multivariate Analysis, Analysis and Applications, Journal of Machine Learning Research and Journal of Semitic Studies.

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.

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