Thomas Gärtner

4.1k citations
89 papers · 1.5k · h-index 18

Impact in

Papers in

Thomas Gärtner

59 papers receiving 1.4k citations

Peers

Thomas Gärtner
Comparison fields: 5 of 144
  • Computer Vision and Pattern Recognition 525
  • Artificial Intelligence 748
  • Computational Theory and Mathematics 302
  • Signal Processing 130
  • Computational Mathematics 6
Replace André Elisseeff with:
André Elisseeff Germany
Hisashi Kashima Japan
M.H.C. Law United States
Liang Chang China
Francesc Serratosa Spain
Pradipta Maji India
José Ruíz-Shulcloper Cuba
Jian-Ping Mei China
Michael Collins United States
Alessandro Sperduti Italy
Thomas Gärtner relative to André Elisseeff Germany André Elisseeff's profile →
Citations per field
00.5×3.7×
André Elisseeff · 1×
Citations per year

Countries citing papers authored by Thomas Gärtner

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Gärtner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Thomas Gärtner, 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 Thomas Gärtner Line = papers co-authored together Thomas Gärtner links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Multi-Instance Kernels
2002295
2 2003256
3 2004170
4 2006116
5 200477
6 201972
7 200846
8 200946
9 200638
10 202137
11 201135
12 202226
13 200825
14 201820
15 200619
16
WBCsvm: Weighted Bayesian Classification based on Support Vector Machines
200118
17 202318
18 201018
19 200815
20 201215

About Thomas Gärtner

Thomas Gärtner is a scholar working on Artificial Intelligence, Anthropology, Computational Theory and Mathematics, Archeology and Classics, having authored 89 papers that have together received 1.5k indexed citations. Recurring topics across this work include Classical Antiquity Studies (19 papers), Historical, Religious, and Philosophical Studies (13 papers), Organic Chemistry Synthesis Methods (9 papers), Computational Drug Discovery Methods (9 papers), Historical, Literary, and Cultural Studies (7 papers), Data Mining Algorithms and Applications (6 papers), Linguistics and language evolution (6 papers) and Machine Learning in Materials Science (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (525 citations), Artificial Intelligence (748 citations), Computational Theory and Mathematics (302 citations), Signal Processing (130 citations) and Computational Mathematics (6 citations). Thomas Gärtner has collaborated with scholars based in Germany, United Kingdom and Austria. Frequent co-authors include Peter Flach, Stefan Wrobel, Alex Smola, Adam Kowalczyk, Tamás Horváth, Ulf Brefeld, Tobias Scheffer, John W. Lloyd, Jürgen Bajorath and Mario Boley. Their work appears in journals such as Machine Learning, Journal of Chemical Information and Modeling, Hermes, Scripta classica Israelica and Emerita.

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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