Robin Tibor Schirrmeister
Robin Tibor Schirrmeister
PhD Candidate, Translational Neurotechnology Lab and Machine Learning Lab, University Freiburg
Verified email at - Homepage
TitleCited byYear
Deep learning with convolutional neural networks for EEG decoding and visualization
RT Schirrmeister, JT Springenberg, LDJ Fiederer, M Glasstetter, ...
Human brain mapping 38 (11), 5391-5420, 2017
Deep learning with convolutional neural networks for decoding and visualization of EEG pathology
R Schirrmeister, L Gemein, K Eggensperger, F Hutter, T Ball
Signal Processing in Medicine and Biology Symposium (SPMB), 2017 IEEE, 1-7, 2017
Acting thoughts: Towards a mobile robotic service assistant for users with limited communication skills
F Burget, LDJ Fiederer, D Kuhner, M Völker, J Aldinger, RT Schirrmeister, ...
Mobile Robots (ECMR), 2017 European Conference on, 1-6, 2017
Compass-based navigation in street networks
S Funke, R Schirrmeister, S Skilevic, S Storandt
International Symposium on Web and Wireless Geographical Information Systems …, 2015
The signature of robot action success in EEG signals of a human observer: Decoding and visualization using deep convolutional neural networks
J Behncke, RT Schirrmeister, W Burgard, T Ball
Brain-Computer Interface (BCI), 2018 6th International Conference on, 1-6, 2018
Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding
KG Hartmann, RT Schirrmeister, T Ball
Brain-Computer Interface (BCI), 2018 6th International Conference on, 1-6, 2018
Deep transfer learning for error decoding from non-invasive EEG
M Völker, RT Schirrmeister, LDJ Fiederer, W Burgard, T Ball
Brain-Computer Interface (BCI), 2018 6th International Conference on, 1-6, 2018
Automatic extrapolation of missing road network data in OpenStreetMap
S Funke, R Schirrmeister, S Storandt
Proceedings of the 2nd International Conference on Mining Urban Data-Volume …, 2015
Neurolinguistic and machine-learning perspectives on direct speech BCIs for restoration of naturalistic communication
O Iljina, J Derix, RT Schirrmeister, A Schulze-Bonhage, P Auer, A Aertsen, ...
Brain-Computer Interfaces 4 (3), 186-199, 2017
Brain Responses During Robot-Error Observation
D Welke, J Behncke, M Hader, RT Schirrmeister, A Schönau, B Eßmann, ...
arXiv preprint arXiv:1708.01465, 2017
Designing and understanding convolutional networks for decoding executed movements from eeg
RT Schirrmeister, LDJ Fiederer, JT Springenberg, M Glasstetter, ...
The First Biannual Neuroadaptive Technology Conference, 143, 2017
Deep Learning for micro-Electrocorticographic ({\mu} ECoG) Data
X Wang, CA Gkogkidis, RT Schirrmeister, FA Heilmeyer, M Gierthmuehlen, ...
arXiv preprint arXiv:1810.02584, 2018
P64. Deep learning for EEG diagnostics
RT Schirrmeister, L Gemein, K Eggensberger, F Hutter, T Ball
Clinical Neurophysiology 129 (8), e94, 2018
The role of robot design in decoding error-related information from EEG signals of a human observer
J Behncke, RT Schirrmeister, W Burgard, T Ball
arXiv preprint arXiv:1807.01597, 2018
Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding
J Behncke, RT Schirrmeister, M Völker, A Schulze-Bonhage, W Burgard, ...
arXiv preprint arXiv:1806.09532, 2018
A framework for large-scale evaluation of deep learning for EEG
FA Heilmeyer, RT Schirrmeister, LDJ Fiederer, M Völker, J Behncke, ...
arXiv preprint arXiv:1806.07741, 2018
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals
KG Hartmann, RT Schirrmeister, T Ball
arXiv preprint arXiv:1806.01875, 2018
Generative Reversible Networks
RT Schirrmeister, P Chrabąszcz, F Hutter, T Ball
arXiv preprint arXiv:1806.01610, 2018
Intracranial Error Detection via Deep Learning
M Völker, J Hammer, RT Schirrmeister, J Behncke, LDJ Fiederer, ...
arXiv preprint arXiv:1805.01667, 2018
Deep Learning Based BCI Control of a Robotic Service Assistant Using Intelligent Goal Formulation
D Kuhner, LDJ Fiederer, J Aldinger, F Burget, M Völker, RT Schirrmeister, ...
bioRxiv, 282848, 2018
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