Matthias Schultheis

Matthias Schultheis joined the Psychology and Information Processing Lab at TU Darmstadt in December 2019 as a PhD student and later continued as a Postdoctoral Researcher until February 2026. He was jointly supervised by Prof. Constantin Rothkopf and Prof. Heinz Koeppl and was also a member of the Self-Organizing Systems (SOS) Lab at TU Darmstadt.

During his PhD, Matthias developed methods for estimating statistical models of sequential decision-making under uncertainty from incomplete behavioral data. He was part of the LOEWE project Whitebox, which focused on explainable models of human and machine intelligence. As a Postdoctoral Researcher, he joined the SCENE project (Simons Collaboration on Ecological Neuroscience), an international collaboration studying how the brain represents and uses information to guide behavior.

• M. Schultheis, J. S. Schönfeld, C. A. Rothkopf, and H. Koeppl (2025). What do you know? Bayesian knowledge inference for navigating agents. In Advances in Neural Information Processing Systems (NeurIPS), 37
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• Straub, D.*, Schultheis, M.*, Koeppl, H., & Rothkopf, C. A. (2023). Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs. In Advances in Neural Information Processing Systems (NeurIPS), 36:7065-7092
  [paper (wird in neuem Tab geöffnet)] [code]
• Schultheis, M., Rothkopf, C. A., & Koeppl, H. (2022). Reinforcement learning with non-exponential discounting. In Advances in Neural Information Processing Systems (NeurIPS), 35:3649-3662.
  [paper (wird in neuem Tab geöffnet)] [code] [talk]
• Schultheis, M.*, Straub, D.*, & Rothkopf, C. A. (2021). Inverse optimal control adapted to the noise characteristics of the human sensorimotor system. In Advances in Neural Information Processing Systems (NeurIPS), 34:9429-9442.
  [paper (wird in neuem Tab geöffnet)] [code] [talk]
• Alt, B., Schultheis, M., & Koeppl, H. (2020). POMDPs in continuous time and discrete spaces. In Advances in Neural Information Processing Systems (NeurIPS), 33:13151-13162.
  [paper (wird in neuem Tab geöffnet)] [code]
• Schultheis, M., Belousov, B., Abdulsamad, H., & Peters, J. (2020). Receding horizon curiosity. In Proceedings of the Conference on Robot Learning (CoRL), 100:1278-1288.
  [paper (wird in neuem Tab geöffnet)] [code]