Wojciech Samek - Google Scholar Citations

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	All	Since 2015
Citations	6065	5791
h-index	31	29
i10-index	70	63

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Co-authors

Klaus-Robert MüllerGoogle Brain (on leave of Professor for Machine Learning, TU Berlin & Korea University, Seoul)Verified email at tu-berlin.de
Alexander BinderAssistant Prof., Singapore University of Technology and Design (SUTD)Verified email at sutd.edu.sg
Grégoire MontavonTechnische Universität BerlinVerified email at tu-berlin.de
Sebastian Lapuschkin (né Bach)Postdoctoral Research Associate, Fraunhofer Heinrich Hertz InstituteVerified email at hhi.fraunhofer.de
Thomas WiegandProfessor, TU Berlin and Fraunhofer HHI, Berlin, GermanyVerified email at tu-berlin.de
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Sebastian BosseFraunhofer HHIVerified email at hhi.fraunhofer.de
Carmen VidaurreBerlin University of Technology, Universidad Pública de NavarraVerified email at unavarra.es
Shinichi NakajimaMachine Learning Group, Technische Universität BerlinVerified email at tu-berlin.de
Frederick KlauschenInstitute of Pathology, Charité Universitätsmedizin BerlinVerified email at charite.de
Sven DähneAmazonVerified email at amazon.com
Nils StrodthoffResearch Scientist, Machine Learning Group, Fraunhofer HHI, GermanyVerified email at hhi.fraunhofer.de
Felix BiessmannEinstein Center for Digital Future, Beuth University, Amazon Research, BerlinVerified email at beuth-hochschule.de
Stephanie BrandlStudent, Berlin Institute of TechnologyVerified email at tu-berlin.de
Frank C. MeineckeResearch Associate, TU BerlinVerified email at tu-berlin.de
Siamac FazliNazarbayev UniversityVerified email at nu.edu.kz
Peter EisertProfessor Visual Computing, Humboldt University Berlin, Fraunhofer HHIVerified email at informatik.hu-berlin.de
Benjamin BlankertzTechnische Universität Berlin, Neurotechnology groupVerified email at tu-berlin.de
Arno VillringerDirector, Max Planck SocietyVerified email at cbs.mpg.de
Stefan HaufeCharité - Universitätsmedizin BerlinVerified email at charite.de

Wojciech Samek

Head of Machine Learning Group, Fraunhofer HHI, Germany

Verified email at hhi.fraunhofer.de - Homepage

Machine Learning Interpretability Deep Learning Explainable AI Federated Learning


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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	1011	2015
Methods for interpreting and understanding deep neural networks G Montavon, W Samek, KR Müller Digital Signal Processing 73, 1-15, 2018	661	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	437	2017
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	357	2017
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models W Samek, T Wiegand, KR Müller ITU Journal: ICT Discoveries - Special Issue 1 - The Impact of Artificial …, 2018	339	2018
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment S Bosse, D Maniry, KR Müller, T Wiegand, W Samek IEEE Transactions on Image Processing 27 (1), 206-219, 2018	267	2018
Stationary common spatial patterns for brain–computer interfacing W Samek, C Vidaurre, KR Müller, M Kawanabe Journal of Neural Engineering 9 (2), 026013, 2012	201	2012
Interpretable deep neural networks for single-trial EEG classification I Sturm, S Lapuschkin, W Samek, KR Müller Journal of Neuroscience Methods 274, 141-145, 2016	157	2016
Divergence-based framework for common spatial patterns algorithms W Samek, M Kawanabe, KR Müller IEEE Reviews in Biomedical Engineering 7, 50-72, 2014	148	2014
Explaining recurrent neural network predictions in sentiment analysis L Arras, G Montavon, KR Müller, W Samek EMNLP'17 Workshop on Computational Approaches to Subjectivity, Sentiment …, 2017	128	2017
"What is relevant in a text document?": An interpretable machine learning approach L Arras, F Horn, G Montavon, KR Müller, W Samek PLOS ONE 12 (8), e0181142, 2017	128	2017
Transferring Subspaces Between Subjects in Brain-Computer Interfacing W Samek, FC Meinecke, KR Müller IEEE Transactions on Biomedical Engineering 60 (8), 2289-2298, 2013	125	2013
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn S Lapuschkin, S Wäldchen, A Binder, G Montavon, W Samek, KR Müller Nature Communications 10, 1096, 2019	123	2019
A deep neural network for image quality assessment S Bosse, D Maniry, T Wiegand, W Samek 23th IEEE International Conference on Image Processing (ICIP), 3773-3777, 2016	116	2016
Analyzing classifiers: Fisher vectors and deep neural networks S Lapuschkin, A Binder, G Montavon, KR Muller, W Samek IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2912-2920, 2016	106	2016
Layer-wise relevance propagation for neural networks with local renormalization layers A Binder, G Montavon, S Lapuschkin, KR Müller, W Samek Artificial Neural Networks and Machine Learning – ICANN 2016, LNCS 9887, 63-71, 2016	86	2016
The LRP toolbox for artificial neural networks S Lapuschkin, A Binder, G Montavon, KR Müller, W Samek Journal of Machine Learning Research 17 (1), 3938-3942, 2016	71	2016
Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain–Computer Interfaces S Fazli, S Dähne, W Samek, F Bießmann, KR Müller Proceedings of the IEEE 103 (6), 891-906, 2015	71	2015
iNNvestigate neural networks! M Alber, S Lapuschkin, P Seegerer, M Hägele, KT Schütt, G Montavon, ... Journal of Machine Learning Research 20 (93), 1-8, 2019	65	2019
Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data S Dähne, F Bießmann, W Samek, S Haufe, D Goltz, C Gundlach, ... Proceedings of the IEEE 103 (9), 1507-1530, 2015	64	2015

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