Hidden Biases of End-to-End Driving Models. - Bernhard Jaeger; Kashyap Chitta; Andreas Geiger 001 (ICCV, 2023)

TransFuser: Imitation With Transformer-Based Sensor Fusion for Autonomous Driving. - Kashyap Chitta; Aditya Prakash 001; Bernhard Jaeger; Zehao Yu 002; Katrin Renz; Andreas Geiger 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers. - Takeru Miyato; Bernhard Jaeger; Max Welling; Andreas Geiger 001 (ICLR, 2024)

Hidden Biases of End-to-End Driving Datasets. - Julian Zimmerlin; Jens Beißwenger; Bernhard Jaeger; Andreas Geiger 001; Kashyap Chitta (CoRR, 2024)

An Invitation to Deep Reinforcement Learning. - Bernhard Jaeger; Andreas Geiger 001 (Found. Trends Optim., 2024)

End-to-End Autonomous Driving: Challenges and Frontiers. - Li Chen 008; Penghao Wu; Kashyap Chitta; Bernhard Jaeger; Andreas Geiger 001; Hongyang Li 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

CaRL: Learning Scalable Planning Policies with Simple Rewards. - Bernhard Jaeger; Daniel Dauner; Jens Beißwenger; Simon Gerstenecker; Kashyap Chitta; Andreas Geiger 001 (CoRR, 2025)