Publications
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Author Keyword Title Type [ Year
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STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning. PLoS Computational Biology. 2014 .
. Emergence of Dynamic Memory Traces in Cortical Microcircuit Models through STDP. The Journal of Neuroscience [Internet]. 2013 ;33:11515-11529. Available from: http://www.jneurosci.org/content/33/28/11515.abstract
. 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
. Learned Muscle Synergies as Prior in Dynamical Systems for Controlling Bio-mechanical and Robotic Systems. In: Abstracts of Neural Control of Movement Conference (NCM 2013). Abstracts of Neural Control of Movement Conference (NCM 2013). ; 2013. Available from: http://eprints.pascal-network.org/archive/00009898/
. Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems. Frontiers in Computational Neuroscience (Special Issue on Modularity in motor control: from muscle synergies to cognitive action representation) [Internet]. 2013 ;7:138. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3797962/
. Stochastic Computations in Cortical Microcircuit Models. PLoS Computational Biology [Internet]. 2013 ;9:e1003311. Available from: http://dx.doi.org/10.1371%2Fjournal.pcbi.1003311
. Emergence of Complex Computational Structures From Chaotic Neural Networks Through Reward-Modulated Hebbian Learning. Cerebral Cortex [Internet]. 2012 . Available from: http://cercor.oxfordjournals.org/content/early/2012/11/09/cercor.bhs348.abstract
. The role of feedback in morphological computation with compliant bodies. Biological Cybernetics [Internet]. 2012 ;106:595-613. Available from: http://dx.doi.org/10.1007/s00422-012-0516-4
. Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation. Artificial Life (Special Issue on Morphological Computation) [Internet]. 2012 ;19:115–131. Available from: http://www.ias.informatik.tu-darmstadt.de/uploads/Site/EditPublication/r%fcckert2012_artificiallife.pdf
. 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/
. Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons. PLoS Computational Biology [Internet]. 2011 ;7:e1002294. Available from: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002294
. 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
. Towards a Theoretical Foundation for Morphological Computation with Compliant Bodies. Biological Cybernetics [Internet]. 2011 ;105:355-370. Available from: http://www.igi.tugraz.at/psfiles/209.pdf
. Variational Inference for Policy Search in Changing Situations. In: 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
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