Jörg Wagner — accepted AI-conference papers

2025

Stochasticity in Motion: An Information-Theoretic Approach to Trajectory Prediction

Aron Distelzweig, Andreas Look, Eitan Kosman, Faris Janjos, Jörg Wagner, Abhinav Valada

IROS 2025

In autonomous driving, accurate motion prediction is crucial for safe and efficient motion planning. To ensure safety, planners require reliable uncertainty estimates of the predicted behavior of surrounding agents, yet this aspect has received limited attention. In particular, decomposing uncertain

Cited by 5 Source ↗Scholar ↗

2016

Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics

Michael Herman, Tobias Gindele, Jörg Wagner, Felix Schmitt, Wolfram Burgard

AISTATS 2016poster

Inverse Reinforcement Learning (IRL) describes the problem of learning an unknown reward function of a Markov Decision Process (MDP) from observed behavior of an agent. Since the agent’s behavior originates in its policy and MDP policies depend on both the stochastic system dynamics as well as the r…

Cited by 89 Source ↗PDF ↗Scholar ↗