Klaus-Robert Müller

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Citations	122120	64734
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Wojciech SamekProfessor at TU Berlin, Head of AI Department at Fraunhofer HHI, BIFOLD FellowVerified email at tu-berlin.de
Benjamin BlankertzTechnische Universität Berlin, Neurotechnology groupVerified email at tu-berlin.de
Grégoire MontavonFreie Universität BerlinVerified email at fu-berlin.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH ZürichVerified email at tuebingen.mpg.de
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Sebastian MikaVerified email at sebastianmika.info
Alexandre TkatchenkoProfessor of Physics, University of Luxembourg; Visiting Professor, TU BerlinVerified email at uni.lu
Alex SmolaBoson AIVerified email at smola.org
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Alexander BinderAssociate Professor, Singapore Institute of Technology (SIT) and University of Oslo (UiO)Verified email at singaporetech.edu.sg
Kristof T. SchüttPfizerVerified email at pfizer.com
Matthias KrauledatRhine-Waal University of Applied SciencesVerified email at hochschule-rhein-waal.de
Andreas ZiehePostdoc researcher, TU BerlinVerified email at cs.tu-berlin.de
Carmen VidaurreIkerbasque Research Associate, Tecnalia, NeurotechVerified email at tecnalia.com
Michael TangermannDonders Insitute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, andVerified email at donders.ru.nl
Guido NolteDept. of Neurophysiology and Pathophysiology, UKE, HamburgVerified email at uke.de
Siamac FazliNazarbayev UniversityVerified email at nu.edu.kz
José del R. MillánCarol Cockrell Curran Endowed Chair Professor, University of Texas at Austin, ECE & NeurologyVerified email at austin.utexas.edu
Huziel E. SaucedaAssistant Professor, Instituto de Física, Universidad Nacional Autonoma de MexicoVerified email at fisica.unam.mx
Claudia SannelliMedtronicVerified email at medtronic.com

Klaus-Robert Müller

TU Berlin & Korea University & Google Brain & Max Planck Institute for Informatics, Germany

Verified email at tu-berlin.de

Machine learning artificial intelligence big data computational neuroscience


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	10432	1998
Efficient backprop Y LeCun, L Bottou, G Orr, KR Müller Neural networks: Tricks of the trade 7700, 9-53, 2012	6428*	2012
An introduction to kernel-based learning algorithms KR Müller, S Mika, G Rätsch, K Tsuda, B Schölkopf IEEE Transactions on Neural Networks 12 (2), 181 - 201, 2001	4818*	2001
Fisher discriminant analysis with kernels S Mika, G Rätsch, J Weston, B Schölkopf, KR Müller Neural Networks for Signal Processing IX, 1999. Proceedings of the 1999 IEEE …, 1999	3798	1999
On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation S Bach, A Binder, G Montavon, F Klauschen, KR Müller, W Samek PloS one 10 (7), e0130140, 2015	3524	2015
Kernel principal component analysis B Schölkopf, A Smola, KR Müller Artificial Neural Networks—ICANN'97, 583-588, 1997	3092*	1997
Methods for interpreting and understanding deep neural networks G Montavon, W Samek, KR Müller Digital Signal Processing 73, 1-15, 2018	2184	2018
Optimizing spatial filters for robust EEG single-trial analysis B Blankertz, R Tomioka, S Lemm, M Kawanabe, KR Müller IEEE Signal processing magazine 25 (1), 41-56, 2008	2133	2008
Fast and accurate modeling of molecular atomization energies with machine learning M Rupp, A Tkatchenko, KR Müller, OA Von Lilienfeld Physical review letters 108 (5), 058301, 2012	1915	2012
Soft margins for AdaBoost G Rätsch, T Onoda, KR Müller Machine learning 42, 287-320, 2001	1682	2001
Input space versus feature space in kernel-based methods B Schölkopf, S Mika, CJC Burges, P Knirsch, KR Müller, G Rätsch, ... IEEE transactions on neural networks 10 (5), 1000-1017, 1999	1662	1999
Kernel PCA and De-noising in feature spaces. S Mika, B Schölkopf, AJ Smola, KR Müller, M Scholz, G Rätsch Advances of Neural Information Processing Systems (NIPS) 11, 536-542, 1998	1373	1998
Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models W Samek, T Wiegand, KR Müller ITU Journal: ICT Discoveries - The Impact of Artifcial Intelligence (AI) on …, 2017	1365	2017
Predicting time series with support vector machines KR Müller, A Smola, G Rätsch, B Schölkopf, J Kohlmorgen, V Vapnik Artificial Neural Networks—ICANN'97, 999-1004, 1997	1362*	1997
Explaining nonlinear classification decisions with deep taylor decomposition G Montavon, S Lapuschkin, A Binder, W Samek, KR Müller Pattern recognition 65, 211-222, 2017	1246	2017
Single-trial analysis and classification of ERP components—a tutorial B Blankertz, S Lemm, M Treder, S Haufe, KR Müller NeuroImage 56 (2), 814-825, 2011	1213	2011
Quantum-chemical insights from deep tensor neural networks KT Schütt, F Arbabzadah, S Chmiela, KR Müller, A Tkatchenko Nature Communications 8, 13890, 2017	1210	2017
Schnet–a deep learning architecture for molecules and materials KT Schütt, HE Sauceda, PJ Kindermans, A Tkatchenko, KR Müller The Journal of Chemical Physics 148 (24), 241722, 2018	1202	2018
How to explain individual classification decisions D Baehrens, T Schroeter, S Harmeling, M Kawanabe, K Hansen, ... Journal of Machine Learning Research 11 (Jun), 1803-1831, 2010	1085	2010
The non-invasive Berlin brain–computer interface: fast acquisition of effective performance in untrained subjects B Blankertz, G Dornhege, M Krauledat, KR Müller, G Curio NeuroImage 37 (2), 539-550, 2007	1052	2007

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