| Bayesian optimization for automated model selection G Malkomes, C Schaff, R Garnett Advances in neural information processing systems 29, 2016 | 134 | 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 | 95 | 2019 |
| Residual policy learning for shared autonomy C Schaff, MR Walter arXiv preprint arXiv:2004.05097, 2020 | 36 | 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 | 21 | 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 | 20 | 2022 |
| A robot cluster for reproducible research in dexterous manipulation S Bauer, F Widmaier, M Wüthrich, N Funk, JUD Jesus, J Peters, J Watson, ... arXiv preprint arXiv:2109.10957, 2021 | 13* | 2021 |
| 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 | 11 | 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 | 3 | 2022 |
| Neural approaches to co-optimization in robotics C Schaff arXiv preprint arXiv:2209.00579, 2022 | 2 | 2022 |
| 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 | 1 | 2023 |
Matthew R. WalterToyota Technological Institute at ChicagoVerified email at ttic.edu
