M. Stetter

85 papers receiving 1.8k citations

Hit Papers

Classifying brain states and determining the discriminati...20052026201220192005100200300400500

Peers

M. Stetter
Comparison fields: 5 of 138
  • Cognitive Neuroscience 653
  • Atomic and Molecular Physics, and Optics 363
  • Radiology, Nuclear Medicine and Imaging 321
  • Electrical and Electronic Engineering 312
  • Molecular Biology 288
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Jr-Shin Li United States
Thomas Lippert Germany
Leigh A. Johnston Australia
Shigeru Tanaka Japan
А. А. Короновский Russia
Arun V. Holden United Kingdom
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E. Harth United States
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Countries citing papers authored by M. Stetter

Since Specialization
Citations

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

Fields of papers citing papers by M. Stetter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Stetter

This figure shows the co-authorship network connecting the top 25 collaborators of M. Stetter. A scholar is included among the top collaborators of M. Stetter 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 M. Stetter. M. Stetter 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
#WorkIndexed citations
1 155
2 17
3
A Knowledge-based Dynamic Bayesian Framework Towards Molecular Network Modeling and Quantitative Prediction.
2
4 18
5
Classifying brain states and determining the discriminating activation patterns: Support Vector Machine on functional MRI databreakdown →
540
6 8
7 4
8
Bayesian Inference of Genetic Networks from Gene-Expression-Data: Convergence and Reliability.
6
9 48
10 18
11 83
12 9
13
Application of Blind Separation of Sources to Optical Recording of Brain Activity
2
14
Modelling Contrast Adaptation and Contextual Effects in Primary Visual Cortex (Invited
2
15 23
16 3
17
Plasma lens focusing of heavy ion beams utilizing a wall-stabilized discharge
0
18 8
19
Optimizing the CERN plasma lens for antiproton collection
1
20 1

About M. Stetter

M. Stetter is a scholar working on Cognitive Neuroscience, Nuclear and High Energy Physics and Atomic and Molecular Physics, and Optics, having authored 89 papers that have together received 1.8k indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (16 papers), Neural dynamics and brain function (15 papers) and Particle accelerators and beam dynamics (13 papers). The work is most often cited by research in Cognitive Neuroscience (653 citations), Nuclear and High Energy Physics (190 citations) and Radiology, Nuclear Medicine and Imaging (321 citations). M. Stetter has collaborated with scholars based in Germany, Spain and United States. Frequent co-authors include Janaı́na Mourão-Miranda, Arun L.W. Bokde, Harald Hampel, Christine Born, J. Christiansen, K. Frank, Klaus Obermayer, Volker Tresp, Hans‐Peter Kriegel and Markus Bundschus. Their work appears in journals such as Applied Physics Letters, Bioinformatics and Journal of Applied 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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