Radar-based Dynamic Occupancy Grid Mapping and Object Detection. - Christopher Diehl; Eduard Feicho; Alexander Schwambach; Thomas Dammeier; Eric Mares; Torsten Bertram (ITSC, 2020)

UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning. - Christopher Diehl; Timo Sievernich; Martin Krüger; Frank Hoffmann 001; Torsten Bertram (CoRR, 2021)

Differentiable Constrained Imitation Learning for Robot Motion Planning and Control. - Christopher Diehl; Janis Adamek; Martin Krüger; Frank Hoffmann 001; Torsten Bertram (CoRR, 2022)

Recognition Beyond Perception: Environmental Model Completion by Reasoning for Occluded Vehicles. - Martin Krüger; Patrick Palmer; Christopher Diehl; Timo Osterburg; Torsten Bertram (IEEE Robotics Autom. Lett., 2022)

Energy-based Potential Games for Joint Motion Forecasting and Control. - Christopher Diehl; Tobias Klosek; Martin Krüger; Nils Murzyn; Timo Osterburg; Torsten Bertram (CoRL, 2023)

On a Connection between Differential Games, Optimal Control, and Energy-based Models for Multi-Agent Interactions. - Christopher Diehl; Tobias Klosek; Martin Krüger; Nils Murzyn; Torsten Bertram (CoRR, 2023)

Uncertainty-Aware Model-Based Offline Reinforcement Learning for Automated Driving. - Christopher Diehl; Timo Sievernich; Martin Krüger; Frank Hoffmann 001; Torsten Bertram (IEEE Robotics Autom. Lett., 2023)

LoRD: Adapting Differentiable Driving Policies to Distribution Shifts. - Christopher Diehl; Péter Karkus; Sushant Veer; Marco Pavone 001; Torsten Bertram (CoRR, 2024)

DIO: Decomposable Implicit 4D Occupancy-Flow World Model. - Christopher Diehl; Quinlan Sykora; Ben Agro; Thomas Gilles; Sergio Casas 002; Raquel Urtasun (CVPR, 2025)

HiLO: High-Level Object Fusion for Autonomous Driving using Transformers. - Timo Osterburg; Franz Albers; Christopher Diehl; Rajesh Pushparaj; Torsten Bertram (CoRR, 2025)