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Number of items: 14.

Paraschos, A. and Rueckert, E. and Peters, J. and Neumann, G. (2018):
Probabilistic Movement Primitives under Unknown System Dynamics.
In: Advanced Robotics, pp. 297-310, 32, (6), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Alumni/AlexandrosPar...],
[Article]

Paraschos, A. and Daniel, C. and Peters, J. and Neumann, G. (2018):
Using Probabilistic Movement Primitives in Robotics.
In: Autonomous Robots, pp. 529-551, 42, (3), ISSN 0929-5593,
[Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/AlexandrosParas...],
[Article]

Dermy, O. and Paraschos, A. and Ewerton, M. and Charpillet, F. and Peters, J. and Ivaldi, S (2017):
Prediction of intention during interaction with iCub with Probabilistic Movement Primitives.
In: Frontiers in Robotics and AI, p. 45, [Online-Edition: https://doi.org/10.3389/frobt.2017.00045],
[Article]

Tanneberg, D. and Paraschos, A. and Peters, J. and Rueckert, E. (2016):
Deep Spiking Networks for Model-based Planning in Humanoids.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/DanielTanneberg...],
[Conference or Workshop Item]

Rueckert, E. and Mundo, J. and Paraschos, A. and Peters, J. and Neumann, G. (2015):
Extracting Low-Dimensional Control Variables for Movement Primitives.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Conference or Workshop Item]

Paraschos, A. and Rueckert, E. and Peters, J and Neumann, G. (2015):
Model-Free Probabilistic Movement Primitives for Physical Interaction.
In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/PubAlexParascho...],
[Conference or Workshop Item]

Parisi, S. and Abdulsamad, H. and Paraschos, A. and Daniel, C. and Peters, J. (2015):
Reinforcement Learning vs Human Programming in Tetherball Robot Games.
In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/SimoneParisi/pa...],
[Conference or Workshop Item]

Neumann, G. and Daniel, C. and Paraschos, A. and Kupcsik, A. and Peters, J. (2014):
Learning Modular Policies for Robotics.
In: Frontiers in Computational Neuroscience, DOI: 10.3389/fncom.2014.00062,
[Online-Edition: http://www.frontiersin.org/Journal/Abstract.aspx?s=237&name=...],
[Article]

Lioutikov, R. and Paraschos, A. and Peters, J. and Neumann, G. (2014):
Generalizing Movements with Information Theoretic Stochastic Optimal Control.
In: Journal of Aerospace Information Systems, pp. 579-595, 11, (9), [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Site/EditPublication/...],
[Article]

Lioutikov, R. and Paraschos, A. and Peters, J. and Neumann, G. (2014):
Sample-Based Information-Theoretic Stochastic Optimal Control.
In: IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 31 - June 7, 2014, [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Team/RudolfLioutikov/...],
[Conference or Workshop Item]

Englert, P. and Paraschos, A. and Peters, J. and Deisenroth, M. P. (2013):
Model-based Imitation Learning by Probabilistic Trajectory Matching.
In: IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, May 6-10, 2013, [Online-Edition: http://www.ias.informatik.tu-darmstadt.de/uploads/Publicatio...],
[Conference or Workshop Item]

Paraschos, A. and Neumann, G. and Peters, J. (2013):
A Probabilistic Approach to Robot Trajectory Generation.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Publications/Parascho...],
[Conference or Workshop Item]

Englert, P. and Paraschos, A. and Peters, J. and Deisenroth, M.P. (2013):
Probabilistic Model-based Imitation Learning.
In: Adaptive Behavior Journal, pp. 388-403, [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Publications/Englert_...],
[Article]

Paraschos, A. and Daniel, C. and Peters, J. and Neumann, G.
Burges, C. J. C. and Bottou, L. and Welling, M. and Ghahramani, Z. and Weinberger, K. Q. (eds.) (2013):
Probabilistic Movement Primitives.
In: Advances in Neural Information Processing Systems (NIPS), Lake Tahoe, Nevada, USA, 5-10 December 2013, In: Advances in Neural Information Processing Systems, 26, [Online-Edition: https://dblp.org/db/conf/nips/nips2013],
[Conference or Workshop Item]

This list was generated on Sat Aug 17 00:39:51 2019 CEST.