most citedManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills

22 citations · 33 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Multi-feature concatenation and multi-classifier stacking: an interpretable and generalizable machine learning method for MDD discrimination with rsfMRI

Yunsong Luo, Wenyu Chen, Ling Zhan +2

Major depressive disorder is a serious and heterogeneous psychiatric disorder that needs accurate diagnosis. Resting-state functional MRI (rsfMRI), which captures multiple perspect…

cs.LG2023

Reparameterized Policy Learning for Multimodal Trajectory Optimization

Zhiao Huang, Litian Liang, Zhan Ling +3

We investigate the challenge of parametrizing policies for reinforcement learning (RL) in high-dimensional continuous action spaces. Our objective is to develop a multimodal policy…

cs.RO20236 cited

On the Efficacy of 3D Point Cloud Reinforcement Learning

Zhan Ling, Yunchao Yao, Xuanlin Li +1

Recent studies on visual reinforcement learning (visual RL) have explored the use of 3D visual representations. However, none of these work has systematically compared the efficacy…

cs.RO202322 cited

ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills

Jiayuan Gu, Fanbo Xiang, Xuanlin Li +12

Generalizable manipulation skills, which can be composed to tackle long-horizon and complex daily chores, are one of the cornerstones of Embodied AI. However, existing benchmarks,…

cs.LG20225 cited

Improving Policy Optimization with Generalist-Specialist Learning

Zhiwei Jia, Xuanlin Li, Zhan Ling +3

Generalization in deep reinforcement learning over unseen environment variations usually requires policy learning over a large set of diverse training variations. We empirically ob…