| 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 | 2181 | 2017 |
| EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals KG Hartmann, RT Schirrmeister, T Ball arXiv preprint arXiv:1806.01875, 2018 | 253 | 2018 |
| Machine-learning-based diagnostics of EEG pathology LAW Gemein, RT Schirrmeister, P Chrabąszcz, D Wilson, J Boedecker, ... NeuroImage 220, 117021, 2020 | 152 | 2020 |
| Understanding anomaly detection with deep invertible networks through hierarchies of distributions and features R Schirrmeister, Y Zhou, T Ball, D Zhang Advances in Neural Information Processing Systems 33, 21038-21049, 2020 | 69 | 2020 |
| Deep transfer learning for error decoding from non-invasive EEG M Völker, RT Schirrmeister, LDJ Fiederer, W Burgard, T Ball 2018 6th International Conference on Brain-Computer Interface (BCI), 1-6, 2018 | 63 | 2018 |
| Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding KG Hartmann, RT Schirrmeister, T Ball 2018 6th International Conference on Brain-Computer Interface (BCI), 1-6, 2018 | 45 | 2018 |
| A service assistant combining autonomous robotics, flexible goal formulation, and deep-learning-based brain–computer interfacing D Kuhner, LDJ Fiederer, J Aldinger, F Burget, M Völker, RT Schirrmeister, ... Robotics and Autonomous Systems 116, 98-113, 2019 | 42 | 2019 |
| 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 2018 6th international conference on brain-computer interface (BCI), 1-6, 2018 | 42 | 2018 |
| 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 | 34 | 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, ... 2017 European Conference on Mobile Robots (ECMR), 1-6, 2017 | 29 | 2017 |
| 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 | 25 | 2015 |
| A large-scale evaluation framework for EEG deep learning architectures FA Heilmeyer, RT Schirrmeister, LDJ Fiederer, M Volker, J Behncke, ... 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 17 | 2018 |
| Intracranial error detection via deep learning M Volker, J Hammer, RT Schirrmeister, J Behncke, LDJ Fiederer, ... 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 12 | 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 | 12 | 2018 |
| Compass-based navigation in street networks S Funke, R Schirrmeister, S Skilevic, S Storandt Web and Wireless Geographical Information Systems: 14th International …, 2015 | 11 | 2015 |
| Brain responses during robot-error observation D Welke, J Behncke, M Hader, RT Schirrmeister, A Schönau, B Eßmann, ... arXiv preprint arXiv:1708.01465, 2017 | 10 | 2017 |
| Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding J Behncke, RT Schirrmeister, M Volker, J Hammer, P Marusic, ... 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 9 | 2018 |
| Training Generative Reversible Networks RT Schirrmeister, P Chrabąszcz, F Hutter, T Ball arXiv preprint arXiv:1806.01610, 2018 | 9 | 2018 |
| Deep learning with convolutional neural networks for decoding and visualization of eeg pathology R Tibor Schirrmeister, L Gemein, K Eggensperger, F Hutter, T Ball arXiv e-prints, arXiv: 1708.08012, 2017 | 8 | 2017 |
| On the importance of hyperparameters and data augmentation for self-supervised learning D Wagner, F Ferreira, D Stoll, RT Schirrmeister, S Müller, F Hutter arXiv preprint arXiv:2207.07875, 2022 | 7 | 2022 |
