Biblio

Found 193 results
Author Title [ Type(Desc)] Year
Search results for Steil  [Reset Search]
Conference Paper
Aswolinskiy W, Reinhart F, Steil JJ.  2015.  Impact of Regularization on the Model Space for Time Series Classification. New Challenges in Neural Computation (NC2). :49–56.
Shareef Z, Mohammadi P, Steil JJ.  2016.  Improving the Inverse Dynamics Model of the KUKA LWR IV+ using Independent Joint Learning. Proceedings 7th IFAC Symposium on Mechatronic Systems. :507––512.
Queißer J, Reinhart F, Steil JJ.  2016.  Incremental Bootstrapping of Parameterized Motor Skills. Proc. IEEE Humanoids.
Denecke A, Wersing H, Steil JJ, Körner E.  2009.  Incremental Figure-Ground Segmentation using localized adaptive metrics in LVQ. International Workshop on Self-Organizing Maps (WSOM). :45–53.
Caluwaerts K, Steil JJ.  2015.  Independent Joint Learning in Practice: Local Error Estimates to Improve Inverse Dynamics Control. :643–650.
Haschke R, Steil JJ.  2004.  Input Space Bifurcation Manifolds of RNNs. Proc. European Symposium Artificial Neural Networks. :13–19.
Steil JJ, Ritter H.  1998.  Input-Output Stability of Recurrent Neural Networks with Delays using Circle Criteria. Proc. Int. ICSC/IFAC Symposium on Neural Computation. :519–525.
Wischnewski M, Steil JJ, Kehrer L, Schneider WX.  2009.  Integrating Inhomogeneous Processing and Proto-object Formation in a Computational Model of Visual Attention. Human Centered Robot Systems: Cognition, Interaction, Technology. :93–102.
Wrede S, Johannfunke M, Lemme A, Nordmann A, Rüther S, Weirich A, Steil JJ.  2010.  Interactive Learning of Inverse Kinematics with Nullspace Constraints using Recurrent Neural Networks. Proc. 20. Workshop on Computational Intelligence.
Emmerich C, Nordmann A, Swadzba A, Wrede S, Steil JJ.  2012.  Interactive Learning of Inverse Kinematics with Null-space Constraints using Recurrent Neural Networks.
Neumann K, Steil JJ.  2012.  Intrinsic Plasticity via Natural Gradient Decent. 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012). Proceedings. :555–560.
Wersing H, Steil JJ, Ritter H.  1997.  A Layered Recurrent Neural Network for Feature Grouping. Int. Conf. on Artificial Neural Networks. :439–444.
Weng S., Steil JJ.  2003.  Learning Compatibitlity Functions for Feature Binding and Perceptual Grouping. Proc. of Int. Conference Artificial Neural Networks. LNCS 2714:60–67.
Rolf M, Steil JJ, Gienger M.  2010.  Learning Flexible Full Body Kinematics for Humanoid Tool Use. Int. Symp. Learning and Adaptive Behavior in Robotic Systems (Best Paper Award). :171–176.
Kubus D, Rayyes R, Steil JJ.  In Press.  Learning Forward and Inverse Kinematics Maps Efficiently. IROS 2018.
Neumann K, Rolf M, Steil JJ, Gienger M.  2010.  Learning Inverse Kinematics for Pose-Constraint Bi-Manual Movements. From Animals to Animats 11. 11th International Conference on Simulation of Adaptive Behavior, SAB 2010. Proceedings. 6226
Weirich A, Haumann C, Steil JJ, Schüler S..  2011.  Learning Lab - Physical Interaction with Humanoid Robots for Pupils. Proc. Robotics in Education. :21–28.
Kober J, Gienger M, Steil JJ.  2015.  Learning Movement Primitives for Force Interaction Tasks. ICRA. :3192–3199.
Soltoggio A, Reinhart F, Lemme A, Steil JJ.  2013.  Learning the rules of a game: neural conditioning in human-robot interaction with delayed rewards.
Freire A, Lemme A, Steil JJ, Baretto G.  2012.  Learning visuo-motor coordination for pointing without depth calculation. Proc. European Symposium on Artificial Neural Networks. :91–96.
Reinhart F, Steil JJ.  2012.  Learning Whole Upper Body Control with Dynamic Redundancy Resolution in Coupled Associative Radial Basis Function Networks. IROS. :1487–1492.
Steil JJ.  2000.  Local input-output stability of recurrent networks with time-varying weights. Proc. European Symposium Artificial Neural Networks. :281–286.
Rolf M, Steil JJ, Gienger M.  2010.  Mastering Growth while Bootstrapping Sensorimotor Coordination. Int. Conf. on Epigenetic Robotics.
Steil JJ, Ritter H.  1999.  Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. Proc. European Symposium Artificial Neural Networks. :369–374.
Steil JJ.  2005.  Memory in Backpropagation-Decorrelation O(N) Efficient Online Recurrent Learning. LNCS. 3697:649–654.

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