K-R Müller
Impact in
- Biomedical Engineering top 5%
- Muscle activation and electromyography studies
- Prosthetics and Rehabilitation Robotics
- Signal Processing top 5%
- Blind Source Separation Techniques
Papers in
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- Blind Source Separation Techniques 4
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- Computational Drug Discovery Methods 3
- Co-authors
- Strahinja S. Dosen (1 shared paper)Ning Jiang (1 shared paper)Dario Farina (1 shared paper)Paul von Bünau (1 shared paper)Duncan A. J. Blythe (1 shared paper)Bernhard Schölkopf (1 shared paper)T. Downs (1 shared paper)AJ Smola (1 shared paper)
- Journals
- Journal of Cheminformatics (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)IEEE Signal Processing Magazine (1 paper)Journal of Neural Engineering (1 paper)Annals of Oncology (1 paper)
- Partner nations
- GermanySouth KoreaSpain
In The Last Decade
K-R Müller
16 papers receiving 551 citations
Peers
Comparison fields: 5 of 51
- Biomedical Engineering 335
- Signal Processing 67
- Human-Computer Interaction 19
- Cognitive Neuroscience 52
- Rehabilitation 11
Countries citing papers authored by K-R Müller
This map shows the geographic impact of K-R Müller'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 K-R Müller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K-R Müller more than expected).
Fields of papers citing papers by K-R Müller
This network shows the impact of papers produced by K-R Müller. 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 K-R Müller. The network helps show where K-R Müller may publish in the future.
Co-authors
The 25 scholars most cited alongside K-R Müller, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 359 | |
| 2 | General cost functions for support vector regression. | 1998 | 57 |
| 3 | 2012 | 42 | |
| 4 | Nonlinear blind source separation using kernel feature spaces | 2001 | 27 |
| 5 | 2009 | 21 | |
| 6 | Separation of post-nonlinear mixtures using ACE and temporal decorrelation | 2001 | 20 |
| 7 | 2021 | 14 | |
| 8 | Blind separation of post-nonlinear mixtures using gaussianizing transformations and temporal decorrelation | 2003 | 12 |
| 9 | 2012 | 9 | |
| 10 | Analysing ICA component by injection noise | 2003 | 2 |
| 11 | 2010 | 2 | |
| 12 | An asymptotical Analysis and Improvement of AdaBoost in the binary classification case | 2000 | 1 |
| 13 | 2004 | 1 | |
| 14 | 2009 | 1 | |
| 15 | 2012 | 1 | |
| 16 | 2022 | 1 |
About K-R Müller
K-R Müller is a scholar working on Signal Processing, Computational Theory and Mathematics, Cognitive Neuroscience, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 16 papers that have together received 570 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (4 papers), EEG and Brain-Computer Interfaces (3 papers), Computational Drug Discovery Methods (3 papers), Machine Learning and Algorithms (2 papers), Imbalanced Data Classification Techniques (1 paper), Muscle activation and electromyography studies (1 paper), AI in cancer detection (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Biomedical Engineering (335 citations), Signal Processing (67 citations), Human-Computer Interaction (19 citations), Cognitive Neuroscience (52 citations) and Rehabilitation (11 citations). K-R Müller has collaborated with scholars based in Germany, South Korea and Spain. Frequent co-authors include Strahinja S. Dosen, Ning Jiang, Dario Farina, Paul von Bünau, Duncan A. J. Blythe, Bernhard Schölkopf, T. Downs, AJ Smola, Marcus Gallagher and Marcus R. Frean. Their work appears in journals such as Journal of Cheminformatics, IEEE Transactions on Neural Networks and Learning Systems, IEEE Signal Processing Magazine, Journal of Neural Engineering and Annals of Oncology.
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.