20 citations · 35 across the 7 of their papers we have counts for
9 papers
SEIL: Simulation-augmented Equivariant Imitation Learning
Mingxi Jia, Dian Wang, Guanang Su +4
In robotic manipulation, acquiring samples is extremely expensive because it often requires interacting with the real world. Traditional image-level data augmentation has shown the…
Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detection
Haojie Huang, Dian Wang, Xupeng Zhu +2
Given point cloud input, the problem of 6-DoF grasp pose detection is to identify a set of hand poses in SE(3) from which an object can be successfully grasped. This important prob…
-Equivariant Reinforcement Learning
Dian Wang, Robin Walters, Robert Platt
Equivariant neural networks enforce symmetry within the structure of their convolutional layers, resulting in a substantial improvement in sample efficiency when learning an equiva…
Sample Efficient Grasp Learning Using Equivariant Models
Xupeng Zhu, Dian Wang, Ondrej Biza +3
In planar grasp detection, the goal is to learn a function from an image of a scene onto a set of feasible grasp poses in . In this paper, we recognize that the opt…
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
Nima Dehmamy, Robin Walters, Yanchen Liu +2
Existing equivariant neural networks require prior knowledge of the symmetry group and discretization for continuous groups. We propose to work with Lie algebras (infinitesimal gen…
Equivariant Learning in Spatial Action Spaces
Dian Wang, Robin Walters, Xupeng Zhu +1
Recently, a variety of new equivariant neural network model architectures have been proposed that generalize better over rotational and reflectional symmetries than standard models…