8 citations · 10 across the 9 of their papers we have counts for
10 papers
Generalizable Hierarchical Skill Learning via Object-Centric Representation
Haibo Zhao, Yu Qi, Boce Hu +9
We present Generalizable Hierarchical Skill Learning (GSL), a novel framework for hierarchical policy learning that significantly improves policy generalization and sample efficien…
Clebsch-Gordan Transformer: Fast and Global Equivariant Attention
Owen Lewis Howell, Linfeng Zhao, Xupeng Zhu +6
The global attention mechanism is one of the keys to the success of transformer architecture, but it incurs quadratic computational costs in relation to the number of tokens. On th…
Recursive Deep Inverse Reinforcement Learning
Paul Ghanem, Owen Howell, Michael Potter +4
Inferring an adversary's goals from exhibited behavior is crucial for counterplanning and non-cooperative multi-agent systems in domains like cybersecurity, military, and strategy…
Hierarchical Equivariant Policy via Frame Transfer
Haibo Zhao, Dian Wang, Yizhe Zhu +6
Recent advances in hierarchical policy learning highlight the advantages of decomposing systems into high-level and low-level agents, enabling efficient long-horizon reasoning and…
NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models
Zhuoran Qiao, Feizhi Ding, Thomas Dresselhaus +10
Structure determination is essential to a mechanistic understanding of diseases and the development of novel therapeutics. Machine-learning-based structure prediction methods have…
Equivariant Action Sampling for Reinforcement Learning and Planning
Linfeng Zhao, Owen Howell, Xupeng Zhu +4
Reinforcement learning (RL) algorithms for continuous control tasks require accurate sampling-based action selection. Many tasks, such as robotic manipulation, contain inherent pro…
Equivariant Offline Reinforcement Learning
Arsh Tangri, Ondrej Biza, Dian Wang +3
Sample efficiency is critical when applying learning-based methods to robotic manipulation due to the high cost of collecting expert demonstrations and the challenges of on-robot p…
k-Fold Gaussian Random Matrix Ensembles I: Forcing Structure into Random Matrices
Michael Brodskiy, Owen L. Howell
Random Matrix Theory is a powerful tool in applied mathematics. Three canonical models of random matrix distributions are the Gaussian Orthogonal, Unitary and Symplectic Ensembles.…
Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D
Haojie Huang, Owen Howell, Dian Wang +3
Many complex robotic manipulation tasks can be decomposed as a sequence of pick and place actions. Training a robotic agent to learn this sequence over many different starting cond…
Multi-Irreducible Spectral Synchronization for Robust Rotation Averaging
Owen Howell, Haoen Huang, David Rosen
Rotation averaging (RA) is a fundamental problem in robotics and computer vision. In RA, the goal is to estimate a set of unknown orientations , gi…