K-R Müller
Impact in
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
- Motor Control and Adaptation
-
- Neuroscience and Neural Engineering
Papers in
-
- Blind Source Separation Techniques 5
- Speech and Audio Processing 2
- Co-authors
- Strahinja Došen (1 shared paper)Dario Farina (1 shared paper)Ning Jiang (1 shared paper)AJ Smola (1 shared paper)Marcus Frean (1 shared paper)Bernhard Schölkopf (1 shared paper)Marcus Gallagher (1 shared paper)T. Downs (1 shared paper)
- Journals
- IEEE Signal Processing Magazine (1 paper)Journal of Neural Engineering (1 paper)Journal of Cheminformatics (1 paper)New Zealand Veterinary Journal (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- GermanySouth KoreaUnited States
In The Last Decade
K-R Müller
15 papers receiving 507 citations
Peers
Comparison fields: 5 of 77
- Cognitive Neuroscience 253
- Cellular and Molecular Neuroscience 208
- Signal Processing 80
- Biomedical Engineering 325
- Human-Computer Interaction 31
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 | 329 | |
| 2 | General cost functions for support vector regression. | 1998 | 58 |
| 3 | 2012 | 34 | |
| 4 | Nonlinear blind source separation using kernel feature spaces | 2001 | 26 |
| 5 | 2009 | 21 | |
| 6 | Separation of post-nonlinear mixtures using ACE and temporal decorrelation | 2001 | 19 |
| 7 | 2021 | 13 | |
| 8 | Blind separation of post-nonlinear mixtures using gaussianizing transformations and temporal decorrelation | 2003 | 12 |
| 9 | 2012 | 8 | |
| 10 | 2016 | 5 | |
| 11 | 2010 | 2 | |
| 12 | An asymptotical Analysis and Improvement of AdaBoost in the binary classification case | 2000 | 1 |
| 13 | 2009 | 1 | |
| 14 | 2004 | 1 | |
| 15 | 2012 | 1 | |
| 16 | Analysing ICA component by injection noise | 2003 | 1 |
About K-R Müller
K-R Müller is a scholar working on Signal Processing, Molecular Biology, Cellular and Molecular Neuroscience, Cognitive Neuroscience and Artificial Intelligence, having authored 16 papers that have together received 532 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (5 papers), Neuroscience and Neural Engineering (3 papers), EEG and Brain-Computer Interfaces (3 papers), Spectroscopy and Chemometric Analyses (3 papers), Muscle activation and electromyography studies (3 papers), Speech and Audio Processing (2 papers), Computational Drug Discovery Methods (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Cognitive Neuroscience (253 citations), Cellular and Molecular Neuroscience (208 citations), Signal Processing (80 citations), Biomedical Engineering (325 citations) and Human-Computer Interaction (31 citations). K-R Müller has collaborated with scholars based in Germany, South Korea and United States. Frequent co-authors include Strahinja Došen, Dario Farina, Ning Jiang, AJ Smola, Marcus Frean, Bernhard Schölkopf, Marcus Gallagher, T. Downs, Duncan A. J. Blythe and Paul von Bünau. Their work appears in journals such as IEEE Signal Processing Magazine, Journal of Neural Engineering, Journal of Cheminformatics, New Zealand Veterinary Journal and IEEE Transactions on Neural Networks and Learning Systems.
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.