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Author Keyword Title Type [ Year(Desc)]
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2011
Hauser H, Neumann G, Ijspeert A, Maass W. Biologically inspired kinematic synergies enable linear balance control of a humanoid robot. Biological Cybernetics [Internet]. 2011 ;104:235–249. Available from: http://www.springerlink.com/content/5217485124776363/
Rückert EA, Neumann G. A study of Morphological Computation by using Probabilistic Inference for Motor Planning. In: 2nd International Conference on Morphological Computation (ICMC2011). 2nd International Conference on Morphological Computation (ICMC2011). Venice, Italy; 2011. pp. 51–53. Available from: http://eprints.pascal-network.org/archive/00008757/01/AICOMorphComp.pdf
Neumann G. Variational Inference for Policy Search in Changing Situations. In: Getoor L, Scheffer T Proceedings of the 28th International Conference on Machine Learning (ICML-11). Proceedings of the 28th International Conference on Machine Learning (ICML-11). New York, NY, USA: ACM; 2011. pp. 817–824. Available from: http://www.igi.tugraz.at/gerhard/research/papers/441_icmlNeumann.pdf
2013
Rückert EA, Neumann G, Toussaint M, Maass W. Learned graphical models for probabilistic planning provide a new class of movement primitives. Frontiers in Computational Neuroscience (Special Issue on Modularity in motor control: from muscle synergies to cognitive action representation) [Internet]. 2013 ;6. Available from: http://www.frontiersin.org/computational_neuroscience/10.3389/fncom.2012.00097/abstract

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