Jakob Thumm

According to our database, Jakob Thumm authored at least 12 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Multi-Objective Causal Bayesian Optimization.

Shriya Bhatija, Paul-David Zürcher, Jakob Thumm, Thomas Bohné

CoRR, February, 2025

2024

A General Safety Framework for Autonomous Manipulation in Human Environments.

Jakob Thumm, Julian Balletshofer, Leonardo Maglanoc, Luis Muschal, Matthias Althoff

CoRR, 2024

Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking.

Roland Stolz, Hanna Krasowski, Jakob Thumm, Michael Eichelbeck, Philipp Gassert, Matthias Althoff

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Human-Robot Gym: Benchmarking Reinforcement Learning in Human-Robot Collaboration.

Jakob Thumm, Felix Trost, Matthias Althoff

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Text2Interaction: Establishing Safe and Preferable Human-Robot Interaction.

Jakob Thumm, Christopher Agia, Marco Pavone, Matthias Althoff

Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024

2023

Provably Safe Reinforcement Learning: Conceptual Analysis, Survey, and Benchmarking.

Hanna Krasowski, Jakob Thumm, Marlon Müller, Lukas Schäfer, Xiao Wang, Matthias Althoff

Trans. Mach. Learn. Res., 2023

Reducing Safety Interventions in Provably Safe Reinforcement Learning.

Jakob Thumm, Guillaume Pelat, Matthias Althoff

IROS, 2023

Approximate First-Passage Time Distributions for Gaussian Motion and Transportation Models.

Marcel Reith-Braun, Florian Pfaff, Jakob Thumm, Uwe D. Hanebeck

Proceedings of the 26th International Conference on Information Fusion, 2023

2022

Mixture of Experts of Neural Networks and Kalman Filters for Optical Belt Sorting.

Jakob Thumm, Marcel Reith-Braun, Florian Pfaff, Uwe D. Hanebeck, Merle Flitter, Georg Maier, Robin Gruna, Thomas Längle, Albert Bauer, Harald Kruggel-Emden

IEEE Trans. Ind. Informatics, 2022

Provably Safe Reinforcement Learning: A Theoretical and Experimental Comparison.

Hanna Krasowski, Jakob Thumm, Marlon Müller, Xiao Wang, Matthias Althoff

CoRR, 2022

Provably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments.

Jakob Thumm, Matthias Althoff

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

SaRA: A Tool for Safe Human-Robot Coexistence and Collaboration through Reachability Analysis.

Sven R. Schepp, Jakob Thumm, Stefan B. Liu, Matthias Althoff

Proceedings of the 2022 International Conference on Robotics and Automation, 2022