Paraschos, A.; Lioutikov, R.; Peters, J.; Neumann, G. (2017). Probabilistic Prioritization of Movement Primitives, Proceedings of the International Conference on Intelligent Robot Systems, and IEEE Robotics and Automation Letters (RA-L).
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Dermy, O.; Paraschos, A.; Ewerton, M.; Charpillet, F.; Peters, J.; Ivaldi, S (2017). Prediction of intention during interaction with iCub with Probabilistic Movement Primitives, Frontiers in Robotics and AI, 4, pp.45.
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Rueckert, E.; Kappel, D.; Tanneberg, D.; Pecevski, D; Peters, J. (2016). Recurrent Spiking Networks Solve Planning Tasks, Nature PG: Scientific Reports, 6, 21142, Nature Publishing Group.
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Rueckert, E.; Camernik, J.; Peters, J.; Babic, J. (2016). Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control, Nature PG: Scientific Reports, 6, 28455.
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Calandra, R.; Seyfarth, A.; Peters, J.; Deisenroth, M. (2015). Bayesian Optimization for Learning Gaits under Uncertainty, Annals of Mathematics and Artificial Intelligence (AMAI).
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Saut, J.-P.; Ivaldi, S.; Sahbani, A.; Bidaud, P. (2014). Grasping objects localized from uncertain point cloud data, Robotics and Autonomous Systems.
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Kohlschuetter, J.; Peters, J.; Rueckert, E. (2016). Learning Probabilistic Features from EMG Data for Predicting Knee Abnormalities, Proceedings of the XIV Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON).
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Modugno, V.; Neumann, G.; Rueckert, E.; Oriolo, G.; Peters, J.; Ivaldi, S. (2016). Learning soft task priorities for control of redundant robots, Proceedings of the International Conference on Robotics and Automation (ICRA).
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Calandra, R.; Peters, J.; Rasmussen, C.E.; Deisenroth, M.P. (2016). Manifold Gaussian Processes for Regression, Proceedings of the International Joint Conference on Neural Networks (IJCNN).
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Weber, P.; Rueckert, E.; Calandra, R.; Peters, J.; Beckerle, P. (2016). A Low-cost Sensor Glove with Vibrotactile Feedback and Multiple Finger Joint and Hand Motion Sensing for Human-Robot Interaction, Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).
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Tanneberg, D.; Paraschos, A.; Peters, J.; Rueckert, E. (2016). Deep Spiking Networks for Model-based Planning in Humanoids, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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Azad, M.; Ortenzi, V.; Lin, H., C.; Rueckert, E.; Mistry, M. (2016). Model Estimation and Control of Complaint Contact Normal Force, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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Calandra, R.; Ivaldi, S.; Deisenroth, M.;Rueckert, E.; Peters, J. (2015). Learning Inverse Dynamics Models with Contacts, Proceedings of the International Conference on Robotics and Automation (ICRA).
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Rueckert, E.; Mundo, J.; Paraschos, A.; Peters, J.; Neumann, G. (2015). Extracting Low-Dimensional Control Variables for Movement Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA).
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Traversaro, S.; Del Prete, A.; Ivaldi, S.; Nori, F. (2015). Avoiding to rely on Inertial Parameters in Estimating Joint Torques with proximal F/T sensing, Proceedings of the International Conference on Robotics and Automation (ICRA).
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Paraschos, A.; Rueckert, E.; Peters, J; Neumann, G. (2015). Model-Free Probabilistic Movement Primitives for Physical Interaction, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
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Rueckert, E.; Lioutikov, R.; Calandra, R.; Schmidt, M.; Beckerle, P.; Peters, J. (2015). Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations, ICRA 2015 Workshop on Tactile and force sensing for autonomous compliant intelligent robots.
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Fritsche, L.; Unverzagt, F.; Peters, J.; Calandra, R. (2015). First-Person Tele-Operation of a Humanoid Robot, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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Calandra, R.; Ivaldi, S.; Deisenroth, M.; Peters, J. (2015). Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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Nori, F.; Peters, J.; Padois, V.; Babic, J.; Mistry, M.; Ivaldi, S. (2014). Whole-body motion in humans and humanoids, Proceedings of the Workshop on New Research Frontiers for Intelligent Autonomous Systems (NRF-IAS), pp.81-92.
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Calandra, R.; Seyfarth, A.; Peters, J.; Deisenroth, M.P. (2014). An Experimental Comparison of Bayesian Optimization for Bipedal Locomotion, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
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Ben Amor, H.; Neumann, G.; Kamthe, S.; Kroemer, O.; Peters, J. (2014). Interaction Primitives for Human-Robot Cooperation Tasks , Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
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Calandra, R.; Gopalan, N.; Seyfarth, A.; Peters, J.; Deisenroth, M.P. (2014). Bayesian Gait Optimization for Bipedal Locomotion, Proceedings of the 2014 Learning and Intelligent Optimization Conference (LION8).
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Kroemer, O.; Peters, J. (2014). Predicting Object Interactions from Contact Distributions, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
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Luck, K.S.; Neumann, G.; Berger, E.; Peters, J.; Ben Amor, H. (2014). Latent Space Policy Search for Robotics, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
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Rueckert, E.; Mindt, M.; Peters, J.; Neumann, G. (2014). Robust Policy Updates for Stochastic Optimal Control, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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Ivaldi, S.; Peters, J.; Padois, V.; Nori, F. (2014). Tools for simulating humanoid robot dynamics: a survey based on user feedback, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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Calandra, R. and Peters, J. and Deisenroth M.P. (2014). Pareto Front Modeling for Sensitivity Analysis in Multi-Objective Bayesian Optimization, NIPS Workshop on Bayesian Optimization 2014.
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Ben Amor, H.; Vogt, D.; Ewerton, M.; Berger, E.; Jung, B.; Peters, J. (2013). Learning Responsive Robot Behavior by Imitation, Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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Paraschos, A.; Neumann, G; Peters, J. (2013). A Probabilistic Approach to Robot Trajectory Generation, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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Berger, E.; Vogt, D.; Haji-Ghassemi, N.; Jung, B.; Ben Amor, H. (2013). Inferring Guidance Information in Cooperative Human-Robot Tasks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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Paraschos, A.; Daniel, C.; Peters, J.; Neumann, G (2013). Probabilistic Movement Primitives, Advances in Neural Information Processing Systems (NIPS), MIT Press.
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Calandra R.; Peters J.; Seyfarth A.; Deisenroth M.P. (2013). An Experimental Evaluation of Bayesian Optimization on Bipedal Locomotion, NIPS 2013 workshop on Bayesian optimization.
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Sharma, D. (2017). Adaptive Training Strategies for Brain Computer Interfaces, Master Thesis.
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Kohlschuetter, J. (2016). Learning Probabilistic Classifiers from Electromyography Data for Predicting Knee Abnormalities, Master Thesis.
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Stark, S. (2016). Learning Probabilistic Feedforward and Feedback Policies for Generating Stable Walking Behaviors, Master Thesis.
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Calandra, R. (2016). Bayesian Modeling for Optimization and Control in Robotics, PhD Thesis.
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Tanneberg, D. (2015). Spiking Neural Networks Solve Robot Planning Problems, Master Thesis.
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Mundo, J. (2014). Extracting Low-Dimensional Control Variables for Movement Primitives, Master Thesis.
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Mindt, M. (2014). Probabilistic Inference for Movement Planning in Humanoids, Master Thesis.
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