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cs.RO2025
HYPE: Hybrid Planning with Ego Proposal-Conditioned Predictions
Hang Yu, Julian Jordan, Julian Schmidt +3
Safe and interpretable motion planning in complex urban environments needs to reason about bidirectional multi-agent interactions. This reasoning requires to estimate the costs of…
cs.RO2025
Evidential Uncertainty Estimation for Multi-Modal Trajectory Prediction
Sajad Marvi, Christoph Rist, Julian Schmidt +2
Accurate trajectory prediction is crucial for autonomous driving, yet uncertainty in agent behavior and perception noise makes it inherently challenging. While multi-modal trajecto…
cs.LG2025
Advancing Out-of-Distribution Detection via Local Neuroplasticity
Alessandro Canevaro, Julian Schmidt, Mohammad Sajad Marvi +3
In the domain of machine learning, the assumption that training and test data share the same distribution is often violated in real-world scenarios, requiring effective out-of-dist…