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Christian Daniel
Christian Daniel
Bosch Center for Artificial Intelligence
Verified email at ias.tu-darmstadt.de
Title
Cited by
Cited by
Year
Probabilistic movement primitives
A Paraschos, C Daniel, JR Peters, G Neumann
Advances in neural information processing systems 26, 2013
7722013
Hierarchical Relative Entropy Policy Search
C Daniel, G Neumann, J Peters
289*
Using probabilistic movement primitives in robotics
A Paraschos, C Daniel, J Peters, G Neumann
Autonomous Robots 42, 529-551, 2018
2412018
Towards learning hierarchical skills for multi-phase manipulation tasks
O Kroemer, C Daniel, G Neumann, H Van Hoof, J Peters
2015 IEEE international conference on robotics and automation (ICRA), 1503-1510, 2015
1562015
Probabilistic inference for determining options in reinforcement learning
C Daniel, H Van Hoof, J Peters, G Neumann
Machine Learning 104, 337-357, 2016
1532016
Probabilistic recurrent state-space models
A Doerr, C Daniel, M Schiegg, D Nguyen-Tuong, S Schaal, M Toussaint, ...
International Conference on Machine Learning (ICML), 2018
1492018
Active Reward Learning.
C Daniel, M Viering, J Metz, O Kroemer, J Peters
Robotics: Science and systems 98, 2014
1492014
Learning step size controllers for robust neural network training
C Daniel, J Taylor, S Nowozin
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
962016
Meta-learning acquisition functions for transfer learning in bayesian optimization
M Volpp, LP Fröhlich, K Fischer, A Doerr, S Falkner, F Hutter, C Daniel
arXiv preprint arXiv:1904.02642, 2019
902019
Active reward learning with a novel acquisition function
C Daniel, O Kroemer, M Viering, J Metz, J Peters
Autonomous Robots 39, 389-405, 2015
722015
Learning concurrent motor skills in versatile solution spaces
C Daniel, G Neumann, J Peters
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2012
552012
Learning sequential motor tasks
C Daniel, G Neumann, O Kroemer, J Peters
2013 IEEE international conference on robotics and automation, 2626-2632, 2013
532013
Optimizing long-term predictions for model-based policy search
A Doerr, C Daniel, D Nguyen-Tuong, A Marco, S Schaal, T Marc, S Trimpe
Conference on Robot Learning, 227-238, 2017
482017
Noisy-input entropy search for efficient robust Bayesian optimization
L Fröhlich, E Klenske, J Vinogradska, C Daniel, M Zeilinger
International Conference on Artificial Intelligence and Statistics, 2262-2272, 2020
352020
SOLO: search online, learn offline for combinatorial optimization problems
J Oren, C Ross, M Lefarov, F Richter, A Taitler, Z Feldman, D Di Castro, ...
Proceedings of the international symposium on combinatorial search 12 (1 …, 2021
332021
BAYESIAN CONTEXT AGGREGATION FOR NEURAL PROCESSES
M Volpp, F Flürenbrock, L Grossberger, C Daniel, G Neumann
332021
Spatio-temporal matching for human pose estimation in video
F Zhou, F De la Torre
IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (8), 1492-1504, 2016
312016
Learning modular policies for robotics
G Neumann, C Daniel, A Paraschos, A Kupcsik, J Peters
Frontiers in computational neuroscience 8, 62, 2014
312014
Differentiable likelihoods for fast inversion of’likelihood-free’dynamical systems
H Kersting, N Krämer, M Schiegg, C Daniel, M Tiemann, P Hennig
International Conference on Machine Learning, 5198-5208, 2020
252020
Reinforcement learning vs human programming in tetherball robot games
S Parisi, H Abdulsamad, A Paraschos, C Daniel, J Peters
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
202015
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