7 citations · 32 across the 33 of their papers we have counts for
4 papers · 1 filter
InsActor: Instruction-driven Physics-based Characters
Jiawei Ren, Mingyuan Zhang, Cunjun Yu +3
Generating animation of physics-based characters with intuitive control has long been a desirable task with numerous applications. However, generating physically simulated animatio…
Decoupled Prioritized Resampling for Offline RL
Yang Yue, Bingyi Kang, Xiao Ma +4
Offline reinforcement learning (RL) is challenged by the distributional shift problem. To address this problem, existing works mainly focus on designing sophisticated policy constr…
Improving and Benchmarking Offline Reinforcement Learning Algorithms
Bingyi Kang, Xiao Ma, Yirui Wang +2
Recently, Offline Reinforcement Learning (RL) has achieved remarkable progress with the emergence of various algorithms and datasets. However, these methods usually focus on algori…
Efficient Diffusion Policies for Offline Reinforcement Learning
Bingyi Kang, Xiao Ma, Chao Du +2
Offline reinforcement learning (RL) aims to learn optimal policies from offline datasets, where the parameterization of policies is crucial but often overlooked. Recently, Diffsuio…