Klaus-Robert Müller

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Citations	129153	71128
h-index	152	113
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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 & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Alexandre TkatchenkoProfessor of Physics, University of Luxembourg; Visiting Professor, TU BerlinVerified email at uni.lu
Sebastian MikaVerified email at sebastianmika.info
Alex SmolaBoson AIVerified email at smola.org
Alexander BinderAssociate Professor, Singapore Institute of Technology (SIT)Verified email at singaporetech.edu.sg
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Andreas ZiehePostdoc researcher, TU BerlinVerified email at cs.tu-berlin.de
Kristof T. SchüttPfizerVerified email at pfizer.com
Matthias KrauledatRhine-Waal University of Applied SciencesVerified email at hochschule-rhein-waal.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
Huziel E. SaucedaAssistant Professor, Instituto de Física, Universidad Nacional Autonoma de MexicoVerified email at fisica.unam.mx
José del R. MillánCarol Cockrell Curran Endowed Chair Professor, University of Texas at Austin, ECE & NeurologyVerified email at austin.utexas.edu
Claudia SannelliMedtronicVerified email at medtronic.com

Klaus-Robert Müller

TU Berlin & Korea University & Google Deepmind & 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	10597	1998
Efficient backprop Y LeCun, L Bottou, G Orr, KR Müller Neural networks: Tricks of the trade 7700, 9-53, 2012	6842*	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	4871*	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	4108	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	3860	2015
Kernel principal component analysis B Schölkopf, A Smola, KR Müller Artificial Neural Networks—ICANN'97, 583-588, 1997	3164	1997
Methods for interpreting and understanding deep neural networks G Montavon, W Samek, KR Müller Digital Signal Processing 73, 1-15, 2018	2384	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	2186	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	2028	2012
Soft margins for AdaBoost G Rätsch, T Onoda, KR Müller Machine learning 42, 287-320, 2001	1701	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	1674	1999
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	1471	2017
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	1414	1998
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	1399	1997
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), 2018	1363	2018
Explaining nonlinear classification decisions with deep taylor decomposition G Montavon, S Lapuschkin, A Binder, W Samek, KR Müller Pattern recognition 65, 211-222, 2017	1356	2017
Quantum-chemical insights from deep tensor neural networks KT Schütt, F Arbabzadah, S Chmiela, KR Müller, A Tkatchenko Nature Communications 8, 13890, 2017	1300	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	1245	2011
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	1150	2010
Evaluating the visualization of what a deep neural network has learned W Samek, A Binder, G Montavon, S Lapuschkin, KR Müller IEEE transactions on neural networks and learning systems 28 (11), 2660-2673, 2017	1137	2017

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