Thomas Gärtner
Impact in
- Artificial Intelligence top 1%
- Advanced Graph Neural Networks
- Text and Document Classification Technologies
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- Graph Theory and Algorithms
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Face and Expression Recognition
Papers in
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- Machine Learning and Algorithms 10
- Neural Networks and Applications 8
- Anthropology 20
- Classical Antiquity Studies 20
- Co-authors
- Peter Flach (5 shared papers)Stefan Wrobel (12 shared papers)Alex Smola (4 shared papers)Adam Kowalczyk (1 shared paper)Tamás Horváth (4 shared papers)John W. Lloyd (2 shared papers)Shankar Vembu (5 shared papers)Mario Boley (8 shared papers)
- Journals
- Machine Learning (4 papers)Hermes (3 papers)Journal of Chemical Information and Modeling (3 papers)Vigiliae Christianae (2 papers)Mnemosyne (2 papers)
- Partner nations
- GermanyUnited KingdomAustria
In The Last Decade
Thomas Gärtner
82 papers receiving 2.7k citations
Thomas Gärtner's Hit Papers
Peers
Comparison fields: 5 of 152
- Artificial Intelligence 1.7k
- Computer Vision and Pattern Recognition 996
- Computational Theory and Mathematics 566
- Signal Processing 281
- Statistical and Nonlinear Physics 218
Countries citing papers authored by Thomas Gärtner
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
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.
All Works
Showing the 20 most-cited of 118 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | On Graph Kernels: Hardness Results and Efficient Alternatives Hit paper breakdown → | 2003 | 621 |
| 2 | Multi-Instance Kernels | 2002 | 353 |
| 3 | 2003 | 349 | |
| 4 | 2004 | 211 | |
| 5 | 2006 | 133 | |
| 6 | 2004 | 120 | |
| 7 | 2003 | 101 | |
| 8 | 2010 | 87 | |
| 9 | 2019 | 72 | |
| 10 | 2009 | 70 | |
| 11 | 2006 | 55 | |
| 12 | 2011 | 53 | |
| 13 | 2008 | 51 | |
| 14 | 2009 | 48 | |
| 15 | 2021 | 38 | |
| 16 | 2008 | 30 | |
| 17 | 2008 | 30 | |
| 18 | 2010 | 27 | |
| 19 | 2022 | 26 | |
| 20 | WBCsvm: Weighted Bayesian Classification based on Support Vector Machines | 2001 | 25 |
About Thomas Gärtner
Thomas Gärtner is a scholar working on Artificial Intelligence, Anthropology, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Archeology, having authored 118 papers that have together received 2.9k indexed citations. Recurring topics across this work include Classical Antiquity Studies (20 papers), Historical, Religious, and Philosophical Studies (14 papers), Computational Drug Discovery Methods (11 papers), Organic Chemistry Synthesis Methods (10 papers), Machine Learning and Algorithms (10 papers), Historical, Literary, and Cultural Studies (9 papers), Neural Networks and Applications (8 papers) and Data Mining Algorithms and Applications (7 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Computer Vision and Pattern Recognition (996 citations), Computational Theory and Mathematics (566 citations), Signal Processing (281 citations) and Statistical and Nonlinear Physics (218 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, John W. Lloyd, Shankar Vembu, Mario Boley, Tobias Scheffer and Ulf Brefeld. Their work appears in journals such as Machine Learning, Hermes, Journal of Chemical Information and Modeling, Vigiliae Christianae and Mnemosyne.
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.