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Charles Schaff
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Cited by
Year
Bayesian optimization for automated model selection
G Malkomes, C Schaff, R Garnett
Advances in Neural Information Processing Systems 29, 2016
902016
Jointly learning to construct and control agents using deep reinforcement learning
C Schaff, D Yunis, A Chakrabarti, MR Walter
2019 International Conference on Robotics and Automation (ICRA), 9798-9805, 2019
572019
Residual policy learning for shared autonomy
C Schaff, MR Walter
arXiv preprint arXiv:2004.05097, 2020
242020
Benchmarking structured policies and policy optimization for real-world dexterous object manipulation
N Funk, C Schaff, R Madan, T Yoneda, JU De Jesus, J Watson, ...
IEEE Robotics and Automation Letters 7 (1), 478-485, 2021
122021
Jointly optimizing placement and inference for beacon-based localization
C Schaff, D Yunis, A Chakrabarti, MR Walter
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems†…, 2017
92017
Grasp and motion planning for dexterous manipulation for the real robot challenge
T Yoneda, C Schaff, T Maeda, M Walter
arXiv preprint arXiv:2101.02842, 2021
82021
A robot cluster for reproducible research in dexterous manipulation
S Bauer, F Widmaier, M WŁthrich, N Funk, JU De Jesus, J Peters, ...
arXiv preprint arXiv:2109.10957, 2021
42021
N-LIMB: Neural Limb Optimization for Efficient Morphological Design
C Schaff, MR Walter
arXiv preprint arXiv:2207.11773, 2022
12022
Soft Robots Learn to Crawl: Jointly Optimizing Design and Control with Sim-to-Real Transfer
C Schaff, A Sedal, MR Walter
arXiv preprint arXiv:2202.04575, 2022
12022
Neural Approaches to Co-Optimization in Robotics
C Schaff
arXiv preprint arXiv:2209.00579, 2022
2022
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Articles 1–10