| Stable output feedback in reservoir computing using ridge regression F Wyffels, B Schrauwen, D Stroobandt International conference on artificial neural networks, 808-817, 2008 | 74 | 2008 |
| A differentiable physics engine for deep learning in robotics J Degrave, M Hermans, J Dambre, F wyffels Frontiers in neurorobotics 13, 6, 2019 | 72 | 2019 |
| A differentiable physics engine for deep learning in robotics J Degrave, M Hermans, J Dambre, F wyffels Frontiers in neurorobotics 13, 6, 2019 | 72 | 2019 |
| A comparative study of reservoir computing strategies for monthly time series prediction F Wyffels, B Schrauwen Neurocomputing 73 (10-12), 1958-1964, 2010 | 64 | 2010 |
| Feedback control by online learning an inverse model T Waegeman, F wyffels, B Schrauwen IEEE transactions on neural networks and learning systems 23 (10), 1637-1648, 2012 | 51 | 2012 |
| Nanophotonic reservoir computing with photonic crystal cavities to generate periodic patterns MAA Fiers, T Van Vaerenbergh, F Wyffels, D Verstraeten, B Schrauwen, ... IEEE transactions on neural networks and learning systems 25 (2), 344-355, 2013 | 39 | 2013 |
| Design and evaluation of a DIY construction system for educational robot kits C Vandevelde, F Wyffels, MC Ciocci, B Vanderborght, J Saldien International Journal of Technology and Design Education 26 (4), 521-540, 2016 | 28 | 2016 |
| Design of a central pattern generator using reservoir computing for learning human motion F Wyffels, B Schrauwen 2009 Advanced Technologies for Enhanced Quality of Life, 118-122, 2009 | 25 | 2009 |
| Band-pass reservoir computing F Wyffels, B Schrauwen, D Verstraeten, D Stroobandt 2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008 | 25 | 2008 |
| Band-pass reservoir computing F Wyffels, B Schrauwen, D Verstraeten, D Stroobandt 2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008 | 25 | 2008 |
| Leveraging robotics research for children with autism: a review LI Ismail, T Verhoeven, J Dambre, F Wyffels International Journal of Social Robotics 11 (3), 389-410, 2019 | 24 | 2019 |
| Morphological properties of mass–spring networks for optimal locomotion learning G Urbain, J Degrave, B Carette, J Dambre, F Wyffels Frontiers in neurorobotics 11, 16, 2017 | 18 | 2017 |
| Frequency modulation of large oscillatory neural networks F wyffels, J Li, T Waegeman, B Schrauwen, H Jaeger Biological cybernetics 108 (2), 145-157, 2014 | 18 | 2014 |
| The spectral radius remains a valid indicator of the echo state property for large reservoirs K Caluwaerts, F Wyffels, S Dieleman, B Schrauwen The 2013 International Joint Conference on Neural Networks (IJCNN), 1-6, 2013 | 18 | 2013 |
| Using reservoir computing in a decomposition approach for time series prediction F wyffels, B Schrauwen, D Stroobandt ESTSP 2008 European Symposium on Time Series Prediction, 149-158, 2008 | 18* | 2008 |
| Transfer learning of gaits on a quadrupedal robot J Degrave, M Burm, PJ Kindermans, J Dambre, F Wyffels Adaptive Behavior 23 (2), 69-82, 2015 | 17 | 2015 |
| Developing an embodied gait on a compliant quadrupedal robot J Degrave, K Caluwaerts, J Dambre, F Wyffels 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 16 | 2015 |
| Do-it-yourself design for social robots: An open-source hardware platform to encourage innovation C Vandevelde, F Wyffels, B Vanderborght, J Saldien IEEE Robotics & Automation Magazine 24 (1), 86-94, 2017 | 15 | 2017 |
| Identifying and removing micro-drift in ground-based electromagnetic induction data P De Smedt, S Delefortrie, F Wyffels Journal of Applied Geophysics 131, 14-22, 2016 | 15 | 2016 |
| Realization of a passive compliant robot dog F Wyffels, M D'Haene, T Waegeman, K Caluwaerts, C Nunes, ... 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and …, 2010 | 14 | 2010 |
Benjamin SchrauwenProfessor of Machine Learning, Ghent UniversityVerified email at ugent.be
