Pierre Schumacher

Orcid: 0009-0006-7369-1836

According to our database1, Pierre Schumacher authored at least 13 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
MIMo: A Multimodal Infant Model for Studying Cognitive Development.
IEEE Trans. Cogn. Dev. Syst., August, 2024

Generating Realistic Arm Movements in Reinforcement Learning: A Quantitative Comparison of Reward Terms and Task Requirements.
CoRR, 2024

Learning to Control Emulated Muscles in Real Robots: Towards Exploiting Bio-Inspired Actuator Morphology.
CoRR, 2024

Identifying Policy Gradient Subspaces.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning to Control Emulated Muscles in Real Robots: A Software Test Bed for Bio-Inspired Actuators in Hardware.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

Quantifying Human Upper Limb Stiffness Responses Based on a Computationally Efficient Neuromusculoskeletal Arm Model.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

Generating Realistic Arm Movements in Reinforcement Learning: A Quantitative Comparison of Reward Terms and Task Requirements.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

2023
MIMo: A Multi-Modal Infant Model for Studying Cognitive Development.
CoRR, 2023

Investigating the Impact of Action Representations in Policy Gradient Algorithms.
CoRR, 2023

Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models.
CoRR, 2023

DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks.
Proceedings of the Conference on Robot Learning, 2022

2021


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