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cs.LG2025
Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning
Sebastian Sanokowski, Kaustubh Patil, Majid Khadiv
Diffusion models provide an expressive framework for sampling from complex, unnormalized distributions. In this work, we extend Maximum Entropy Reinforcement Learning (ME-RL) to di…
cs.RO2025
E2E Parking Dataset: An Open Benchmark for End-to-End Autonomous Parking
Kejia Gao, Liguo Zhou, Mingjun Liu +1
End-to-end learning has shown great potential in autonomous parking, yet the lack of publicly available datasets limits reproducibility and benchmarking. While prior work introduce…