3 papers
cs.LG2024
Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments
Runfa Chen, Ling Wang, Yu Du +4
Learning policies for multi-entity systems in 3D environments is far more complicated against single-entity scenarios, due to the exponential expansion of the global state space as…
cs.CV2024
Equivariant Local Reference Frames for Unsupervised Non-rigid Point Cloud Shape Correspondence
Ling Wang, Runfa Chen, Yikai Wang +6
Unsupervised non-rigid point cloud shape correspondence underpins a multitude of 3D vision tasks, yet itself is non-trivial given the exponential complexity stemming from inter-poi…
cs.LG2023
Subequivariant Graph Reinforcement Learning in 3D Environments
Runfa Chen, Jiaqi Han, Fuchun Sun +1
Learning a shared policy that guides the locomotion of different agents is of core interest in Reinforcement Learning (RL), which leads to the study of morphology-agnostic RL. Howe…