Thomas Hotz

39 papers receiving 611 citations

Peers

Thomas Hotz
Comparison fields: 5 of 96
  • Structural Biology 21
  • Geometry and Topology 125
  • Signal Processing 109
  • Biophysics 45
  • Statistics and Probability 48
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K. Scherer Germany
Estelle Kuhn France
Nien Fan Zhang United States
Tauseef Ur Rehman United States
Triet Le United States
G. D. Taylor United States
Søren Jensen United States
Zenonas Navickas Lithuania
Ronald W. Shonkwiler United States
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Countries citing papers authored by Thomas Hotz

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Hotz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Intrinsic shape analysis: Geodesic principal component analysis for Riemannian manifolds modulo Lie group actions. Discussion paper with rejoinder.
201072
2 201271
3 200356
4 200855
5 201244
6 199937
7 200933
8 201132
9 201426
10 201224
11 201119
12 201319
13 201115
14 201413
15 201813
16 201111
17 200811
18 201811
19 202310
20 20139

About Thomas Hotz

Thomas Hotz is a scholar working on Geometry and Topology, Signal Processing, Artificial Intelligence, Computational Mechanics and Surgery, having authored 43 papers that have together received 653 indexed citations. Recurring topics across this work include Morphological variations and asymmetry (12 papers), Bayesian Methods and Mixture Models (6 papers), Biometric Identification and Security (4 papers), Petri Nets in System Modeling (3 papers), Advanced Statistical Methods and Models (3 papers), Sparse and Compressive Sensing Techniques (3 papers), Soil Geostatistics and Mapping (3 papers) and Statistical and numerical algorithms (3 papers). The work is most often cited by research in Structural Biology (21 citations), Geometry and Topology (125 citations), Signal Processing (109 citations), Biophysics (45 citations) and Statistics and Probability (48 citations). Thomas Hotz has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Stephan Huckemann, Axel Munk, K Käch, Mark Rudin, Dieter Cadosch, René Zellweger, M Decurtins, Andreas Schönle, Stefan W. Hell and Alexander Egner. Their work appears in journals such as Journal of the Royal Statistical Society Series C (Applied Statistics), IEEE Transactions on Pattern Analysis and Machine Intelligence, Bioinformatics, Journal of Orthopaedic Trauma and IEEE Transactions on NanoBioscience.

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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