| Stability-based validation of clustering solutions T Lange, V Roth, ML Braun, JM Buhmann Neural computation 16 (6), 1299-1323, 2004 | 608 | 2004 |
| The need for open source software in machine learning S Sonnenburg, ML Braun, CS Ong, S Bengio, L Bottou, G Holmes, ... JMLR 8, 2443-2466, 2007 | 256 | 2007 |
| Improving human performance in a real operating environment through real-time mental workload detection J Kohlmorgen, G Dornhege, M Braun, B Blankertz, KR Müller, G Curio, ... Toward brain-computer interfacing 409422, 409-422, 2007 | 233 | 2007 |
| A resampling approach to cluster validation V Roth, T Lange, M Braun, J Buhmann Proc. Computational Statistics (CompStat’02, Berlin, Germany), 123-128, 2002 | 190 | 2002 |
| On relevant dimensions in kernel feature spaces ML Braun, JM Buhmann, KR Müller The Journal of Machine Learning Research 9, 1875-1908, 2008 | 158 | 2008 |
| Stability-based model selection T Lange, M Braun, V Roth, J Buhmann Advances in neural information processing systems 15, 2002 | 148 | 2002 |
| Kernel Analysis of Deep Networks. G Montavon, ML Braun, KR Müller Journal of Machine Learning Research 12 (9), 2011 | 145 | 2011 |
| Accurate error bounds for the eigenvalues of the kernel matrix ML Braun The Journal of Machine Learning Research 7, 2303-2328, 2006 | 76 | 2006 |
| Hidden markov anomaly detection N Görnitz, M Braun, M Kloft International conference on machine learning, 1833-1842, 2015 | 66 | 2015 |
| Analyzing local structure in kernel-based learning: Explanation, complexity, and reliability assessment G Montavon, ML Braun, T Krueger, KR Muller IEEE Signal Processing Magazine 30 (4), 62-74, 2013 | 49 | 2013 |
| Fast cross-validation via sequential testing. T Krueger, D Panknin, ML Braun J. Mach. Learn. Res. 16 (1), 1103-1155, 2015 | 48 | 2015 |
| Kernelizing PLS, degrees of freedom, and efficient model selection N Krämer, ML Braun Proceedings of the 24th international conference on Machine learning, 441-448, 2007 | 42 | 2007 |
| Spectral properties of the kernel matrix and their relation to kernel methods in machine learning ML Braun Universitäts-und Landesbibliothek Bonn, 2005 | 36 | 2005 |
| Learning and evaluation in presence of non-iid label noise N Görnitz, A Porbadnigk, A Binder, C Sannelli, M Braun, KR Müller, ... Artificial Intelligence and Statistics, 293-302, 2014 | 32 | 2014 |
| Estimating noise and dimensionality in BCI data sets: towards illiteracy comprehension C Sannelli, M Braun, M Tangermann, KR Müller na 1, 1-6, 2008 | 31 | 2008 |
| Improving BCI performance by task-related trial pruning C Sannelli, M Braun, KR Müller Neural Networks 22 (9), 1295-1304, 2009 | 26 | 2009 |
| Toward brain-computer interfacing J Kohlmorgen, G Dornhege, M Braun, B Blankertz, KR Müller, G Curio, ... MIT Press, 2007 | 26 | 2007 |
| Stability-based model order selection in clustering with applications to gene expression data V Roth, ML Braun, T Lange, JM Buhmann Artificial Neural Networks—ICANN 2002: International Conference Madrid …, 2002 | 24 | 2002 |
| Layer-wise analysis of deep networks with gaussian kernels G Montavon, KR Müller, M Braun Advances in neural information processing systems 23, 2010 | 19 | 2010 |
| Extracting latent brain states—Towards true labels in cognitive neuroscience experiments AK Porbadnigk, N Görnitz, C Sannelli, A Binder, M Braun, M Kloft, ... NeuroImage 120, 225-253, 2015 | 18 | 2015 |
Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
