20 citations · 46 across the 28 of their papers we have counts for
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cs.LG2019★ 20 cited
Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network
Chen Tang, Jianyu Chen, Masayoshi Tomizuka
Probabilistic vehicle trajectory prediction is essential for robust safety of autonomous driving. Current methods for long-term trajectory prediction cannot guarantee the physical…
cs.LG2019★ 8 cited
ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations
Daniel Seita, David Chan, Roshan Rao +3
Learning from demonstrations is a popular tool for accelerating and reducing the exploration requirements of reinforcement learning. When providing expert demonstrations to human s…