Sven Dähne

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Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyCorreu electrònic verificat a tu-berlin.de
Benjamin BlankertzTechnische Universität Berlin, Neurotechnology groupCorreu electrònic verificat a tu-berlin.de
Stefan HaufeTechnische Universität Berlin, Physikalisch-Technische Bundesanstalt, Charité - UniversitätsmedizinCorreu electrònic verificat a tu-berlin.de
Pieter-Jan KindermansStaff Research Scientist, Google DeepmindCorreu electrònic verificat a google.com
Felix BiessmannEinstein Center Digital Future, Berlin University of Applied SciencesCorreu electrònic verificat a bht-berlin.de
Frank C. MeineckeDirector of Applied Machine Learning, TomTomCorreu electrònic verificat a tomtom.com
Kristof T. SchüttPfizer, Machine Learning ResearchCorreu electrònic verificat a pfizer.com
Michael TangermannDonders Insitute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, andCorreu electrònic verificat a donders.ru.nl
Maximilian AlberTU BerlinCorreu electrònic verificat a tu-berlin.de
Kai GörgenBCCN Berlin, Science of Intelligence, Charite University Hospital BerlinCorreu electrònic verificat a bccn-berlin.de
John-Dylan HaynesProfessor for Theory and Analysis of Large-Scale Brain Signals, Charite - Universitätsmedizin Berlin, GermanyCorreu electrònic verificat a bccn-berlin.de
Johannes HöhneData Science @ BayerCorreu electrònic verificat a bayer.com
Wojciech SamekProfessor at TU Berlin, Head of AI Department at Fraunhofer HHI, BIFOLD FellowCorreu electrònic verificat a tu-berlin.de
Matthias Schultze-KraftPostDoc, Bernstein Center for Computational Neuroscience, BerlinCorreu electrònic verificat a bccn-berlin.de
Vadim V NikulinPrincipal Investigator, Max Planck Institute for Human Cognitive and Brain SciencesCorreu electrònic verificat a cbs.mpg.de
Dumitru ErhanDirector of Research @ Google DeepMindCorreu electrònic verificat a google.com
Been KimGoogle DeepMindCorreu electrònic verificat a csail.mit.edu
Martijn SchreuderANT NeuroCorreu electrònic verificat a ant-neuro.com
Siamac FazliNazarbayev UniversityCorreu electrònic verificat a nu.edu.kz
Han-Jeong HwangAssociate Professor, Dept of Electronics and Information Engineering, Korea University, SejongCorreu electrònic verificat a korea.ac.kr

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Amazon

Correu electrònic verificat a amazon.com

machine learning data science neuroimaging neuroscience


Títol Ordena per cites Ordena per any Ordena per títol	Citada per Citada per	Any
On the interpretation of weight vectors of linear models in multivariate neuroimaging S Haufe, F Meinecke, K Görgen, S Dähne, JD Haynes, B Blankertz, ... Neuroimage 87, 96-110, 2014	1399	2014
The (un) reliability of saliency methods PJ Kindermans, S Hooker, J Adebayo, M Alber, KT Schütt, S Dähne, ... Explainable AI: Interpreting, explaining and visualizing deep learning, 267-280, 2019	831	2019
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	446	2019
Learning how to explain neural networks: Patternnet and patternattribution PJ Kindermans, KT Schütt, M Alber, KR Müller, D Erhan, B Kim, S Dähne arXiv preprint arXiv:1705.05598, 2017	425	2017
The point of no return in vetoing self-initiated movements M Schultze-Kraft, D Birman, M Rusconi, C Allefeld, K Görgen, S Dähne, ... Proceedings of the national Academy of Sciences 113 (4), 1080-1085, 2016	313	2016
The Berlin brain-computer interface: progress beyond communication and control B Blankertz, L Acqualagna, S Dähne, S Haufe, M Schultze-Kraft, I Sturm, ... Frontiers in neuroscience 10, 530, 2016	250	2016
Investigating the influence of noise and distractors on the interpretation of neural networks PJ Kindermans, K Schütt, KR Müller, S Dähne arXiv preprint arXiv:1611.07270, 2016	152	2016
SPoC: A novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters S Dähne, FC Meinecke, S Haufe, J Höhne, M Tangermann, KR Müller, ... NeuroImage 86, 111-122, 2014	152	2014
Effect of higher frequency on the classification of steady-state visual evoked potentials DO Won, HJ Hwang, S Dähne, KR Müller, SW Lee Journal of neural engineering 13 (1), 016014, 2015	124	2015
Concurrent Adaptation of Human and Machine Improves Simultaneous and Proportional Myoelectric Control J Hahne, S Dähne, HJ Hwang, KR Müller, L Parra IEEE Transactions on Neural Systems and Rehabilitation Engineering 23 (4 …, 2015	117	2015
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	110	2015
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	107	2015
User-centered design in brain–computer interfaces—A case study M Schreuder, A Riccio, M Risetti, S Dähne, A Ramsay, J Williamson, ... Artificial intelligence in medicine 59 (2), 71-80, 2013	101	2013
Dimensionality reduction for the analysis of brain oscillations S Haufe, S Dähne, VV Nikulin NeuroImage 101, 583-597, 2014	94	2014
Pyff–a pythonic framework for feedback applications and stimulus presentation in neuroscience B Venthur, S Scholler, J Williamson, S Dähne, MS Treder, MT Kramarek, ... Frontiers in Neuroscience 4, 2010	83	2010
Natural stimuli improve auditory BCIs with respect to ergonomics and performance J Höhne, K Krenzlin, S Dähne, M Tangermann Journal of Neural Engineering 9 (4), 045003, 2012	79	2012
EEG predictors of covert vigilant attention A Martel, S Dähne, B Blankertz Journal of neural engineering 11 (3), 035009, 2014	77	2014
Finding brain oscillations with power dependencies in neuroimaging data S Dähne, VV Nikulin, D Ramírez, PJ Schreier, KR Müller, S Haufe NeuroImage 96, 334-348, 2014	57	2014
Multi-variate EEG analysis as a novel tool to examine brain responses to naturalistic music stimuli I Sturm, S Dähne, B Blankertz, G Curio PloS one 10 (10), e0141281, 2015	53	2015
Patternnet and patternlrp–improving the interpretability of neural networks PJ Kindermans, KT Schütt, M Alber, KR Müller, S Dähne arXiv preprint arXiv:1705.05598 3, 2017	46	2017

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