Markus Maier

501 citations
4 papers · 188 · h-index 4

Impact in

Papers in

Journals
Theoretical Computer Science (1 paper)ESAIM Probability and Statistics (1 paper)Max Planck Institute for Plasma Physics (2 papers)
Partner nations
Germany

In The Last Decade

Markus Maier

4 papers receiving 176 citations

Peers

Markus Maier
Comparison fields: 5 of 42
  • Computer Vision and Pattern Recognition 87
  • Artificial Intelligence 114
  • Statistical and Nonlinear Physics 36
  • Signal Processing 20
  • Media Technology 16
Replace Vassilis Kalofolias with:
Vassilis Kalofolias Switzerland
Huaijun Qiu China
Xiyang Luo United States
Roi Livni Israel
Olga Gerasimova Russia
Adam Woźnica Switzerland
Seyed Amjad Seyedi Iran
Robert Gens United States
C. E. Veni Madhavan India
Yi Wen China
Markus Maier relative to Vassilis Kalofolias Switzerland Vassilis Kalofolias's profile →
Citations per field
00.5×1.5×
Vassilis Kalofolias · 1×
Citations per year

Countries citing papers authored by Markus Maier

Since Specialization
Citations

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

Fields of papers citing papers by Markus Maier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 2 scholars most cited alongside Markus Maier, 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 Markus Maier Line = papers co-authored together Markus Maier links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1
Influence of graph construction on graph-based clustering measures
2008103
2 200964
3 201217
4
Manifold denoising as preprocessing for finding natural representations of data
20074

About Markus Maier

Markus Maier is a scholar working on Artificial Intelligence, Geometry and Topology, Statistical and Nonlinear Physics, Signal Processing and Ocean Engineering, having authored 4 papers that have together received 188 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (2 papers), Complex Network Analysis Techniques (2 papers), Graph theory and applications (2 papers), Data Management and Algorithms (1 paper), Automated Road and Building Extraction (1 paper), Time Series Analysis and Forecasting (1 paper), Neural Networks and Applications (1 paper) and Topological and Geometric Data Analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (87 citations), Artificial Intelligence (114 citations), Statistical and Nonlinear Physics (36 citations), Signal Processing (20 citations) and Media Technology (16 citations). Markus Maier has collaborated with scholars based in Germany. Frequent co-authors include Matthias Hein and Ulrike von Luxburg. Their work appears in journals such as Theoretical Computer Science, ESAIM Probability and Statistics and Max Planck Institute for Plasma Physics.

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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