How Rich Motor Skills Empower Robots at Last: Insights and Progress of the AMARSi Project. KI- Künstliche Intelligenz. 26:407–410.. 2012.
Interactive Imitation Learning of Object Movement Skills. Autonomous Robots. 32:97–114.. 2012.
Interactive Learning of Inverse Kinematics with Null-space Constraints using Recurrent Neural Networks.. 2012.
Intrinsic Plasticity via Natural Gradient Decent. 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012). Proceedings. :555–560.. 2012.
Learning visuo-motor coordination for pointing without depth calculation. Proc. European Symposium on Artificial Neural Networks. :91–96.. 2012.
Learning Whole Upper Body Control with Dynamic Redundancy Resolution in Coupled Associative Radial Basis Function Networks. IROS. :1487–1492.. 2012.
Online learning and generalization of parts-based image representations by Non-Negative Sparse Autoencoders. Neural Networks. 33:194–203.. 2012.
Regularization and stability in reservoir networks with output feedback. Neurocomputing. 90:96–105.. 2012.
Regularization by Intrinsic Plasticity and its Synergies with Recurrence for Random Projection Methods. Journal of Intelligent Learning Systems and Applications. 4:230–246.. 2012.
Representation and Generalization of Bi-manual Skills from Kinesthetic Teaching. IEEE-RAS International Conference on Humanoid Robots. :560–567.. 2012.
Teaching Nullspace Constraints in Physical Human-Robot Interaction using Reservoir Computing. International Conference on Robotics and Automation. :1868–1875.. 2012.
Batch Intrinsic Plasticity for Extreme Learning Machines. Artificial Neural Networks and Machine Learning – ICANN 2011. Pt. 1. 6791:339–346.. 2011.
A constrained regularization approach for input-driven recurrent neural networks. Differential Equations and Dynamical Systems. 19:27–46.. 2011.
Integrating Feature Maps and Competitive Layer Architectures For Motion Segmentation. Neurocomputing. 74:1372–1381.. 2011.
Learning Lab - Physical Interaction with Humanoid Robots for Pupils. Proc. Robotics in Education. :21–28.. 2011.
Manual Intelligence as a Rosetta Stone for Robot Cognition. Robotics Research. 66:135–146.. 2011.
Neural learning and dynamical selection of redundant solutions for inverse kinematic control. Proc. IEEE Int. Conf. Humanoid Robots. :564–569.. 2011.
Online Goal Babbling for rapid bootstrapping of inverse models in high dimensions. IEEE Int. Conf. Development and Learning and on Epigenetic Robotics (best student paper award). 2:1–8.. 2011.
Reservoir regularization stabilizes learning of Echo State Networks with output feedback. Proc. European Symposium on Artificial Neural Networks. :59–64.. 2011.
Robot with automatic selection of task-specific representations for imitation learning. European Patent Office.. 2011.
State prediction: a constructive method to program recurrent neural networks. Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. 6791:159–166.. 2011.
What do humanoid robots offer to experimental psychology ? Connectionist models of neurocognition and emergent behavior : from theory to applications ; proceedings of the 12th Neural Computation and Psychology Workshop, Birkbeck, University of London, 8 - 10 April 2010. 20:361–371.. 2011.