Sven Dähne
Sven Dähne
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TitleCited byYear
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
5152014
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
1272016
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
872019
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
792017
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
782014
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
762016
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
652015
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
602013
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
592015
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
582012
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
512010
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
442015
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
422014
Dimensionality reduction for the analysis of brain oscillations
S Haufe, S Dähne, VV Nikulin
NeuroImage 101, 583-597, 2014
382014
EEG predictors of covert vigilant attention
A Martel, S Dähne, B Blankertz
Journal of neural engineering 11 (3), 035009, 2014
372014
Optimized stimulation events for a visual ERP BCI
M Tangermann, M Schreuder, S Dähne, J Höhne, S Regler, A Ramsay, ...
Int. J. Bioelectromagn 13 (3), 119-120, 2011
332011
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
312015
Integration of multivariate data streams with bandpower signals
S Dähne, F Bießmann, FC Meinecke, J Mehnert, S Fazli, KR Muller
Multimedia, IEEE Transactions on 15 (5), 1001-1013, 2013
282013
Patternnet and patternlrp–improving the interpretability of neural networks
PJ Kindermans, KT Schütt, M Alber, KR Müller, S Dähne
stat 1050, 16, 2017
262017
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
242019
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