Wojciech Samek

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Citations	28345	26946
h-index	61	60
i10-index	139	125

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Klaus-Robert MüllerTU Berlin & Korea University & Google Deepmind & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
Sebastian LapuschkinHead of Explainable AI, Fraunhofer Heinrich Hertz InstituteVerified email at hhi.fraunhofer.de
Grégoire MontavonFreie Universität BerlinVerified email at fu-berlin.de
Alexander BinderAssociate Professor, Singapore Institute of Technology (SIT)Verified email at singaporetech.edu.sg
Thomas WiegandProfessor, TU Berlin and Fraunhofer HHI, Berlin, GermanyVerified email at tu-berlin.de
Sebastian BosseHead of Interactive & Cognitive Systems, Fraunhofer HHI, GermanyVerified email at hhi.fraunhofer.de
Felix SattlerFraunhofer Heinrich Hertz InstituteVerified email at hhi.fraunhofer.de
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Frederick KlauschenInstitute of Pathology, University of Munich (LMU)Verified email at lmu.de
Leila ArrasResearch Associate, Fraunhofer HHI, BIFOLD, Berlin, GermanyVerified email at hhi.fraunhofer.de
Nils StrodthoffProfessor for eHealth/AI4Health, Oldenburg University, GermanyVerified email at uol.de
Vignesh SrinivasanFraunhofer HHIVerified email at hhi.fraunhofer.de
Shinichi NakajimaMachine Learning Group, Technische Universität BerlinVerified email at tu-berlin.de
Carmen VidaurreIkerbasque Research Associate, BCBL & BIFOLD TU-BerlinVerified email at bcbl.eu
Sven DähneAmazonVerified email at amazon.com
Arno VillringerDirector, Max Planck SocietyVerified email at cbs.mpg.de
Peter EisertProfessor Visual Computing, Humboldt University Berlin, Fraunhofer HHIVerified email at informatik.hu-berlin.de
Felix BiessmannEinstein Center Digital Future, Berlin University of Applied SciencesVerified email at bht-berlin.de
Benjamin BlankertzTechnische Universität Berlin, Neurotechnology groupVerified email at tu-berlin.de

Wojciech Samek

Professor at TU Berlin, Head of AI Department at Fraunhofer HHI, BIFOLD Fellow

Verified email at tu-berlin.de - Homepage

Deep Learning Interpretability Explainable AI Trustworthy AI Federated Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	4060	2015
Methods for interpreting and understanding deep neural networks G Montavon, W Samek, KR Müller Digital Signal Processing 73, 1-15, 2018	2483	2018
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models W Samek, T Wiegand, KR Müller ITU Journal: ICT Discoveries 1 (1), 39-48, 2018	1526	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	1411	2017
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	1191	2020
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	1184	2017
Explainable AI: Interpreting, explaining and visualizing deep learning W Samek, G Montavon, A Vedali, LK Hansen, KR Müller Lecture Notes in Computer Science, Springer 11700, 1-439, 2019	1064	2019
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	986	2019
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	945	2018
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications W Samek, G Montavon, S Lapuschkin, CJ Anders, KR Müller Proceedings of the IEEE 109 (3), 247-278, 2021	776*	2021
Layer-Wise Relevance Propagation: An Overview G Montavon, A Binder, S Lapuschkin, W Samek, KR Müller Explainable AI: Interpreting, Explaining and Visualizing Deep Learning 11700 …, 2019	669	2019
A unifying review of deep and shallow anomaly detection L Ruff, JR Kauffmann, RA Vandermeulen, G Montavon, W Samek, M Kloft, ... Proceedings of the IEEE 109 (5), 756-795, 2021	656	2021
Clustered federated learning: Model-agnostic distributed multi-task optimization under privacy constraints F Sattler, KR Müller, W Samek IEEE Transactions on Neural Networks and Learning Systems 32 (8), 3710-3722, 2021	643	2021
Towards explainable artificial intelligence W Samek, KR Müller Explainable AI: Interpreting, Explaining and Visualizing Deep Learning 11700 …, 2019	528	2019
PTB-XL, a large publicly available electrocardiography dataset P Wagner, N Strodthoff, RD Bousseljot, D Kreiseler, FI Lunze, W Samek, ... Scientific Data 7 (1), 1-15, 2020	462	2020
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	401	2016
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	394	2017
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	388	2016
Artificial Intelligence in Dentistry: Chances and Challenges F Schwendicke, W Samek, J Krois Journal of Dental Research 99 (7), 769-774, 2020	385	2020
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	366	2019

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