Bayesian optimization for automated model selection. - Gustavo Malkomes; Chip Schaff; Roman Garnett (AutoML@ICML, 2016)

Jointly optimizing placement and inference for beacon-based localization. - Charles B. Schaff; David Yunis; Ayan Chakrabarti; Matthew R. Walter (IROS, 2017)

Jointly Learning to Construct and Control Agents using Deep Reinforcement Learning. - Charles B. Schaff; David Yunis; Ayan Chakrabarti; Matthew R. Walter (ICRA, 2019)

Residual Policy Learning for Shared Autonomy. - Charles B. Schaff; Matthew R. Walter (Robotics: Science and Systems, 2020)

Grasp and Motion Planning for Dexterous Manipulation for the Real Robot Challenge. - Takuma Yoneda; Charles B. Schaff; Takahiro Maeda 001; Matthew R. Walter (CoRR, 2021)

A Robot Cluster for Reproducible Research in Dexterous Manipulation. - Stefan Bauer; Felix Widmaier; Manuel Wüthrich; Niklas Funk; Julen Urain De Jesus; Jan Peters 001; Joe Watson; Claire Chen; Krishnan Srinivasan; Junwu Zhang; Jeffrey Zhang 005; Matthew R. Walter; et al. (CoRR, 2021)

Soft Robots Learn to Crawl: Jointly Optimizing Design and Control with Sim-to-Real Transfer. - Charles B. Schaff; Audrey Sedal; Matthew R. Walter (Robotics: Science and Systems, 2022)

N-LIMB: Neural Limb Optimization for Efficient Morphological Design. - Charles B. Schaff; Matthew R. Walter (CoRR, 2022)

Neural Approaches to Co-Optimization in Robotics. - Charles B. Schaff (CoRR, 2022)

Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation. - Niklas Funk; Charles B. Schaff; Rishabh Madan; Takuma Yoneda; Julen Urain De Jesus; Joe Watson; Ethan K. Gordon; Felix Widmaier; Stefan Bauer; Siddhartha S. Srinivasa; Tapomayukh Bhattacharjee; Matthew R. Walter; et al. (IEEE Robotics Autom. Lett., 2022)

Sim-to-real transfer of co-optimized soft robot crawlers. - Charles B. Schaff; Audrey Sedal; Shiyao Ni; Matthew R. Walter (Auton. Robots, 2023)