Biblio
] .
2014. Neural Learning of Vector Fields for Encoding Stable Dynamical Systems. Neurocomputing. 141:3–14.
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2013. Neurally imprinted stable vector fields. ESANN. :327–332.
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2012. Online learning and generalization of parts-based image representations by Non-Negative Sparse Autoencoders. Neural Networks. 33:194–203.
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2013. Rare neural correlations implement robotic conditioning with reward delays and disturbances. Frontiers in Neurorobotics. 7:6.
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2009. Reaching movement generation with a recurrent neural network based on learning inverse kinematics for the humanoid robot iCub. IEEE Conf. Humanoid Robotics. :323–330.
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2010. Recurrence Enhances the Spatial Encoding of Static Inputs in Reservoir Networks. Proc. Int. Conf. Artificial Neural Networks. :148–153.
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2008. Recurrent neural associative learning of forward and inverse kinematics for movement generation of the redundant PA-10 robot. Int. Symp. Learning Adaptive Behavior in Robotic Systems, best paper award. 1:35–40.
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2012. Regularization and stability in reservoir networks with output feedback. Neurocomputing. 90:96–105.
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2012. Representation and Generalization of Bi-manual Skills from Kinesthetic Teaching. IEEE-RAS International Conference on Humanoid Robots. :560–567.
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2011. Reservoir regularization stabilizes learning of Echo State Networks with output feedback. Proc. European Symposium on Artificial Neural Networks. :59–64.
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2014. Semi-supervised Bootstrapping of a Movement Primitive Library from Complex Trajectories. :726–732.
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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.
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2010. Tacking reduces bow-diving of high-speed unmanned sea surface vehicles. Int. Symp. Learning and Adaptive Behavior in Robotic Systems. :177–182.
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2016. Time Series Classification in Reservoir- and Model-Space: A Comparison. Proc. 7th IAPR Workshop on Artificial Neural Networks in Pattern Recognition.
