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2020 – today
- 2023
[c21]Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann:
Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference. ICLR 2023- 2021
- [c20]Michael Volpp, Fabian Flürenbrock, Lukas Großberger
, Christian Daniel, Gerhard Neumann:
Bayesian Context Aggregation for Neural Processes. ICLR 2021 - [c19]Joel Oren, Chana Ross, Maksym Lefarov, Felix Richter, Ayal Taitler, Zohar Feldman, Dotan Di Castro, Christian Daniel:
SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems. SOCS 2021: 97-105 - [i6]Joel Oren, Chana Ross, Maksym Lefarov, Felix Richter, Ayal Taitler, Zohar Feldman, Christian Daniel, Dotan Di Castro:
SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems. CoRR abs/2104.01646 (2021) - 2020
- [c18]Lukas P. Fröhlich, Edgar D. Klenske, Julia Vinogradska, Christian Daniel, Melanie N. Zeilinger:
Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization. AISTATS 2020: 2262-2272 - [c17]Michael Volpp, Lukas P. Fröhlich, Kirsten Fischer, Andreas Doerr, Stefan Falkner, Frank Hutter, Christian Daniel:
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization. ICLR 2020 - [c16]Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig:
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems. ICML 2020: 5198-5208 - [i5]Lukas P. Fröhlich, Edgar D. Klenske, Christian G. Daniel, Melanie N. Zeilinger:
Bayesian Optimization for Policy Search in High-Dimensional Systems via Automatic Domain Selection. CoRR abs/2001.07394 (2020) - [i4]Lukas P. Fröhlich, Edgar D. Klenske, Julia Vinogradska, Christian Daniel, Melanie N. Zeilinger:
Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization. CoRR abs/2002.02820 (2020) - [i3]Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig:
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems. CoRR abs/2002.09301 (2020)
2010 – 2019
- 2019
- [c15]Andreas Doerr, Michael Volpp, Marc Toussaint, Sebastian Trimpe, Christian Daniel:
Trajectory-Based Off-Policy Deep Reinforcement Learning. ICML 2019: 1636-1645 - [c14]Lukas P. Fröhlich, Edgar D. Klenske, Christian G. Daniel, Melanie N. Zeilinger:
Bayesian Optimization for Policy Search in High-Dimensional Systems via Automatic Domain Selection. IROS 2019: 757-764 - [i2]Michael Volpp, Lukas P. Fröhlich, Andreas Doerr, Frank Hutter, Christian Daniel:
Meta-Learning Acquisition Functions for Bayesian Optimization. CoRR abs/1904.02642 (2019) - [i1]Andreas Doerr, Michael Volpp, Marc Toussaint, Sebastian Trimpe, Christian Daniel:
Trajectory-Based Off-Policy Deep Reinforcement Learning. CoRR abs/1905.05710 (2019) - 2018
- [j5]Alexandros Paraschos, Christian Daniel, Jan Peters, Gerhard Neumann:
Using probabilistic movement primitives in robotics. Auton. Robots 42(3): 529-551 (2018) - [c13]Andreas Doerr, Christian Daniel, Martin Schiegg, Duy Nguyen-Tuong, Stefan Schaal, Marc Toussaint, Sebastian Trimpe:
Probabilistic Recurrent State-Space Models. ICML 2018: 1279-1288 - 2017
- [c12]Andreas Doerr, Christian Daniel, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Marc Toussaint, Sebastian Trimpe:
Optimizing Long-term Predictions for Model-based Policy Search. CoRL 2017: 227-238 - 2016
- [b1]Christian Daniel:
Learning hierarchical policies from human ratings. Darmstadt University of Technology, Germany, 2016, pp. 1-123 - [j4]Christian Daniel, Gerhard Neumann, Oliver Kroemer, Jan Peters:
Hierarchical Relative Entropy Policy Search. J. Mach. Learn. Res. 17: 93:1-93:50 (2016) - [j3]Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann:
Probabilistic inference for determining options in reinforcement learning. Mach. Learn. 104(2-3): 337-357 (2016) - [c11]Christian Daniel, Jonathan Taylor, Sebastian Nowozin:
Learning Step Size Controllers for Robust Neural Network Training. AAAI 2016: 1519-1525 - [c10]Christian Scheifele, Armin Lechler, Christian Daniel, Weiliang Xu:
Real-time extension of ROS based on a network of modular blocks for highly precise motion generation. AMC 2016: 129-134 - 2015
- [j2]Christian Daniel, Oliver Kroemer, Malte Viering, Jan Metz, Jan Peters:
Active reward learning with a novel acquisition function. Auton. Robots 39(3): 389-405 (2015) - [c9]Oliver Kroemer, Christian Daniel, Gerhard Neumann, Herke van Hoof, Jan Peters:
Towards learning hierarchical skills for multi-phase manipulation tasks. ICRA 2015: 1503-1510 - [c8]Simone Parisi, Hany Abdulsamad, Alexandros Paraschos, Christian Daniel, Jan Peters:
Reinforcement learning vs human programming in tetherball robot games. IROS 2015: 6428-6434 - 2014
- [j1]Gerhard Neumann, Christian Daniel, Alexandros Paraschos, Andras Gabor Kupcsik, Jan Peters:
Learning modular policies for robotics. Frontiers Comput. Neurosci. 8: 62 (2014) - [c7]Christian Daniel, Malte Viering, Jan Metz, Oliver Kroemer, Jan Peters:
Active Reward Learning. Robotics: Science and Systems 2014 - 2013
- [c6]Christian Daniel, Gerhard Neumann, Oliver Kroemer, Jan Peters:
Learning sequential motor tasks. ICRA 2013: 2626-2632 - [c5]Christian Daniel, Gerhard Neumann, Jan Peters:
Autonomous reinforcement learning with hierarchical REPS. IJCNN 2013: 1-8 - [c4]Alexandros Paraschos, Christian Daniel, Jan Peters, Gerhard Neumann:
Probabilistic Movement Primitives. NIPS 2013: 2616-2624 - 2012
- [c3]Christian Daniel, Gerhard Neumann, Jan Peters:
Learning concurrent motor skills in versatile solution spaces. IROS 2012: 3591-3597 - [c2]Christian Daniel, Gerhard Neumann, Jan Peters:
Hierarchical Relative Entropy Policy Search. AISTATS 2012: 273-281 - 2010
- [c1]Alécio Pedro Delazari Binotto, Christian Daniel, Daniel Weber, Arjan Kuijper, André Stork, Carlos Eduardo Pereira, Dieter W. Fellner:
Iterative SLE Solvers over a CPU-GPU Platform. HPCC 2010: 305-313
Coauthor Index
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