| Bayesian optimization for automated model selection G Malkomes, C Schaff, R Garnett Advances in neural information processing systems 29, 2016 | 153 | 2016 |
| 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 | 130 | 2019 |
| Residual policy learning for shared autonomy C Schaff, MR Walter arXiv preprint arXiv:2004.05097, 2020 | 46 | 2020 |
| 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 | 37 | 2021 |
| 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 | 30 | 2022 |
| Real robot challenge: A robotics competition in the cloud S Bauer, M Wüthrich, F Widmaier, A Buchholz, S Stark, A Goyal, ... NeurIPS 2021 Competitions and Demonstrations Track, 190-204, 2022 | 18* | 2022 |
| 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 | 14 | 2017 |
| 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 | 10 | 2021 |
| N-limb: Neural limb optimization for efficient morphological design C Schaff, MR Walter arXiv preprint arXiv:2207.11773, 2022 | 5 | 2022 |
| Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation. IEEE Robotics and Automation Letters, 7 (1), 478–485 N Funk, C Schaff, R Madan, T Yoneda, JU De Jesus, J Watson, ... | 5 | 2021 |
| Sim-to-real transfer of co-optimized soft robot crawlers C Schaff, A Sedal, S Ni, MR Walter Autonomous Robots 47 (8), 1195-1211, 2023 | 4 | 2023 |
| Neural approaches to co-optimization in robotics C Schaff arXiv preprint arXiv:2209.00579, 2022 | 2 | 2022 |
| RATE CONTROL MACHINE LEARNING MODELS WITH FEEDBACK CONTROL FOR VIDEO ENCODING C Gu, H Mao, C Chiang, C Chen, J Han, CYD Pang, RA Claus, ... US Patent App. 18/791,975, 2024 | | 2024 |
| Rate control machine learning models with feedback control for video encoding C Gu, H Mao, CH Chiang, C Chen, J Han, CYD Pang, RA Claus, ... US Patent 12,088,823, 2024 | | 2024 |
Matthew R. WalterToyota Technological Institute at ChicagoOverená e-mailová adresa na: ttic.edu