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pro vyhledávání: '"Su, Huangyuan"'
Autor:
Villaflor, Adam, Yang, Brian, Su, Huangyuan, Fragkiadaki, Katerina, Dolan, John, Schneider, Jeff
Significant progress has been made in training multimodal trajectory forecasting models for autonomous driving. However, effectively integrating these models with downstream planners and model-based control approaches is still an open problem. Althou
Externí odkaz:
http://arxiv.org/abs/2403.07232
Autor:
Yang, Brian, Su, Huangyuan, Gkanatsios, Nikolaos, Ke, Tsung-Wei, Jain, Ayush, Schneider, Jeff, Fragkiadaki, Katerina
Diffusion models excel at modeling complex and multimodal trajectory distributions for decision-making and control. Reward-gradient guided denoising has been recently proposed to generate trajectories that maximize both a differentiable reward functi
Externí odkaz:
http://arxiv.org/abs/2402.06559
Deep reinforcement learning (DRL) gives the promise that an agent learns good policy from high-dimensional information, whereas representation learning removes irrelevant and redundant information and retains pertinent information. In this work, we d
Externí odkaz:
http://arxiv.org/abs/2205.14557
During the training of a reinforcement learning (RL) agent, the distribution of training data is non-stationary as the agent's behavior changes over time. Therefore, there is a risk that the agent is overspecialized to a particular distribution and i
Externí odkaz:
http://arxiv.org/abs/2109.10552