Andreas Geiger

Latest

• LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving
• ReSim: Reliable World Simulation for Autonomous Driving
• CaRL: Learning Scalable Planning Policies with Simple Rewards
• Pseudo-Simulation for Autonomous Driving
• SHRED: Synthesizing Rule-Based Environments for Driving
• Open X-AV: Unifying End-to-End Autonomous Driving Datasets
• NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking