Matthias Rottmann

739 total citations
28 papers, 244 citations indexed

About

Matthias Rottmann is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Matthias Rottmann has authored 28 papers receiving a total of 244 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 9 papers in Computational Theory and Mathematics. Recurrent topics in Matthias Rottmann's work include Matrix Theory and Algorithms (6 papers), Adversarial Robustness in Machine Learning (5 papers) and Advanced Neural Network Applications (5 papers). Matthias Rottmann is often cited by papers focused on Matrix Theory and Algorithms (6 papers), Adversarial Robustness in Machine Learning (5 papers) and Advanced Neural Network Applications (5 papers). Matthias Rottmann collaborates with scholars based in Germany, Switzerland and United States. Matthias Rottmann's co-authors include Hanno Gottschalk, Robin Chan, Karsten Kahl, Andreas Frommer, Constantia Alexandrou, Simone Bacchio, Jacob Finkenrath, Tilo Wettig, Peter Schlicht and Fabian Hüger and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Journal of Medicinal Chemistry.

In The Last Decade

Matthias Rottmann

23 papers receiving 237 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Matthias Rottmann Germany 8 84 82 79 15 15 28 244
J. Ngadiuba United States 8 119 1.4× 99 1.2× 53 0.7× 6 0.4× 9 0.6× 19 252
S. Summers Switzerland 7 52 0.6× 63 0.8× 44 0.6× 5 0.3× 10 0.7× 15 173
V.K. Agrawal India 5 13 0.2× 170 2.1× 35 0.4× 2 0.1× 20 1.3× 13 255
Peter Schichtel Germany 10 403 4.8× 60 0.7× 14 0.2× 3 0.2× 3 0.2× 21 496
Qunli Xia China 10 7 0.1× 34 0.4× 34 0.4× 8 0.5× 6 0.4× 53 267
N.D. Rao Canada 12 17 0.2× 32 0.4× 8 0.1× 9 0.6× 11 0.7× 65 454
Mason Ng United States 9 36 0.4× 17 0.2× 40 0.5× 18 1.2× 1 0.1× 33 351
Takeshi Yamasaki Japan 12 7 0.1× 27 0.3× 135 1.7× 9 0.6× 18 1.2× 40 455
Stefan Meiser Germany 6 34 0.4× 35 0.4× 103 1.3× 1 0.1× 43 2.9× 7 275
Debing Zhang China 7 33 0.4× 33 0.4× 179 2.3× 2 0.1× 25 285

Countries citing papers authored by Matthias Rottmann

Since Specialization
Citations

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

Fields of papers citing papers by Matthias Rottmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Rottmann

This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Rottmann. A scholar is included among the top collaborators of Matthias Rottmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthias Rottmann. Matthias Rottmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Klein, Saskia K., Laís Pessanha de Carvalho, Larissa A. Meyer, et al.. (2025). Structure–Activity Relationships of 3-Hydroxypropanamidines (HPAs) with Potent In Vivo Antimalarial Activity. Journal of Medicinal Chemistry. 68(18). 19229–19248.
2.
Diamanti, Eleonora, Mostafa M. Hamed, Natalie Wiedemar, et al.. (2025). A Novel Antimalarial Agent that Inhibits Protein Synthesis in Plasmodium falciparum. Angewandte Chemie International Edition. 64(49). e202514085–e202514085. 1 indexed citations
3.
Kahl, Karsten, et al.. (2025). LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds. International Journal of Computer Vision. 133(7). 4349–4365. 1 indexed citations
4.
Rottmann, Matthias, Olusola Ajibaye, Julius Mulindwa, et al.. (2025). The Importance of Murine Models in Determining In Vivo Pharmacokinetics, Safety, and Efficacy in Antimalarial Drug Discovery. Pharmaceuticals. 18(3). 424–424.
5.
Nekrasov, A. N., et al.. (2025). OoDIS: Anomaly Instance Segmentation and Detection Benchmark. 2764–2771.
6.
Kahl, Karsten, et al.. (2024). Deep Active Learning with Noisy Oracle in Object Detection. 375–384.
7.
Rottmann, Matthias, et al.. (2023). Detection of Iterative Adversarial Attacks via Counter Attack. Journal of Optimization Theory and Applications. 198(3). 892–929. 1 indexed citations
8.
Gottschalk, Hanno, et al.. (2023). A convenient infinite dimensional framework for generative adversarial learning. Electronic Journal of Statistics. 17(1). 1 indexed citations
9.
Rottmann, Matthias, et al.. (2023). Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3910–3920. 6 indexed citations
10.
Rottmann, Matthias, et al.. (2023). Prediction Quality Meta Regression and Error Meta Classification for Segmented Lidar Point Clouds. International Journal of Artificial Intelligence Tools. 32(5).
11.
Rottmann, Matthias, et al.. (2022). HD Lane Map Generation Based on Trail Map Aggregation. 2022 IEEE Intelligent Vehicles Symposium (IV). 600–606. 2 indexed citations
12.
Rottmann, Matthias, et al.. (2022). Background-foreground segmentation for interior sensing in automotive industry. SHILAP Revista de lepidopterología. 12(1). 2 indexed citations
13.
Bracke, Stefan, et al.. (2020). Detecting Out of Distribution Objects in Semantic Segmentation of Street Scenes. Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference. 3023–3030. 3 indexed citations
14.
Chan, Robin, Matthias Rottmann, Hanno Gottschalk, Fabian Hüger, & Peter Schlicht. (2020). Application of Maximum Likelihood Decision Rules for Handling Class Imbalance in Semantic Segmentation. Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference. 3065–3072. 8 indexed citations
15.
Chan, Robin, Matthias Rottmann, Fabian Hüger, Peter Schlicht, & Hanno Gottschalk. (2020). Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. 1–8. 6 indexed citations
16.
17.
Rottmann, Matthias. (2018). Adaptive Domain Decomposition Multigrid for Lattice QCD. 2 indexed citations
18.
Wettig, Tilo, et al.. (2016). Adaptive algebraic multigrid on SIMD architectures. 36–36. 23 indexed citations
19.
Brannick, James, et al.. (2015). Multigrid preconditioning for the overlap operator in lattice QCD. Numerische Mathematik. 132(3). 463–490. 15 indexed citations
20.
Rottmann, Matthias, Andreas Frommer, Karsten Kahl, Stefan Krieg, & Björn Leder. (2012). Aggregation-based Multilevel Methods for Lattice QCD. 46–46. 1 indexed citations

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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