Klaus-Robert Müller

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Citations	132971	74705
h-index	155	114
i10-index	529	406

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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 Berlin; APS Fellow; FRSCVerified email at uni.lu
Sebastian MikaVerified email at sebastianmika.info
Alexander BinderAssociate Professor, Singapore Institute of Technology (SIT)Verified email at singaporetech.edu.sg
Alex SmolaBoson AIVerified email at smola.org
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Kristof T. SchüttPfizer, Machine Learning ResearchVerified email at pfizer.com
Andreas ZiehePostdoc researcher, TU BerlinVerified email at cs.tu-berlin.de
Frank C. MeineckeDirector of Applied Machine Learning, TomTomVerified email at tomtom.com
Carmen VidaurreIkerbasque Research Associate, BCBL & BIFOLD TU-BerlinVerified email at bcbl.eu
Matthias KrauledatRhine-Waal University of Applied SciencesVerified email at hochschule-rhein-waal.de
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
Huziel E. SaucedaAssistant Professor, Instituto de Física, Universidad Nacional Autonoma de MexicoVerified email at fisica.unam.mx
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

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	10702	1998
Efficient backprop Y LeCun, L Bottou, G Orr, KR Müller Neural networks: Tricks of the trade 7700, 9-53, 2012	6957*	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	4911*	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	4139	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	4083	2015
Kernel principal component analysis B Schölkopf, A Smola, KR Müller Artificial Neural Networks—ICANN'97, 583-588, 1997	3223	1997
Methods for interpreting and understanding deep neural networks G Montavon, W Samek, KR Müller Digital Signal Processing 73, 1-15, 2018	2502	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	2229	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	2103	2012
Soft margins for AdaBoost G Rätsch, T Onoda, KR Müller Machine learning 42, 287-320, 2001	1711	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	1695	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	1538	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), 2018	1474	2018
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	1425	1998
Explaining nonlinear classification decisions with deep taylor decomposition G Montavon, S Lapuschkin, A Binder, W Samek, KR Müller Pattern recognition 65, 211-222, 2017	1421	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	1414	1997
Quantum-chemical insights from deep tensor neural networks KT Schütt, F Arbabzadah, S Chmiela, KR Müller, A Tkatchenko Nature Communications 8, 13890, 2017	1348	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	1259	2011
Robust and communication-efficient federated learning from non-iid data F Sattler, S Wiedemann, KR Müller, W Samek IEEE transactions on neural networks and learning systems 31 (9), 3400--3413, 2020	1210	2020
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	1196	2010

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