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Grollman DH, Billard A. Donut as I do: Learning from Failed Demonstrations. In: International Conference on Robotics and Automation. International Conference on Robotics and Automation. Shanghai; 2011. Available from: https://ais.informatik.uni-freiburg.de/files/grollman11icra.pdf
Giese MA. Biological and Body Motion Perception. The Oxford Handbook of Perceptual Organisation (Forthcoming) [Internet]. 2014 . Available from: http://www.oxfordhandbooks.com/10.1093/oxfordhb/9780199686858.001.0001/oxfordhb-9780199686858-e-008
Gentner R, Edmunds T, Pai DK, d'Avella A. Robustness of muscle synergies during visuomotor adaptation. Frontiers in Computational Neuroscience [Internet]. 2013 ;7:120. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3759787/
Gay S, Santos-Victor J, Ijspeert A. Learning robot gait stability using neural networks as sensory feedback function for Central Pattern Generators. In: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on. Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on. IEEE; 2013.
Gaspers J, Panzner M, Lemme A, Cimiano P, Rohlfing KJ, Wrede S. A multi-modal corpus for evaluation of computational models for (grounded) language acquisition process. In: EACL, Workshop on Cognitive Aspects of Computer Language Learning. EACL, Workshop on Cognitive Aspects of Computer Language Learning. ; 2014.
Gan DM, Tsagarakis NG, Dai JS, Caldwell DG. Stiffness Design Tuning for Compliant Robots: Protecting the Robot under Accidental Impacts. In: 13th World Congress in Mechanism and Machine Science. 13th World Congress in Mechanism and Machine Science. Washington, DC; 2011.
Gan DM, Tsagarakis NG, Dai JS, Caldwell DG. Joint Stiffness Tuning for Compliant Robots: Protecting the Robot under Accidental Impacts. In: 13th World Congress in Mechanism and Machine Science,2011. 13th World Congress in Mechanism and Machine Science,2011. ; 2011. Available from: http://somim.org.mx/conference_proceedings/pdfs/A23/A23_501.pdf
Galtier M, Touboul J. Macroscopic Equations Governing Noisy Spiking Neuronal Populations with Linear Synapses. PLOS one. 2013 ;8:e78917. (888.85 KB)
Galtier MN, Marini C, Wainrib G, Jaeger H. Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes. Neural Networks [Internet]. 2014 ;56:10-21. Available from: http://arxiv.org/abs/1402.1613
Galtier M, Wainrib G. A biological gradient descent for prediction through a combination of STDP and homeostatic plasticity. Neural Computation [Internet]. 2013 ;25(11). Available from: http://de.arxiv.org/abs/1206.4812

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