5 papers
Beyond Topology: A Morphological Symmetry Graph Representation for Locomotion Policy Learning
Sizhe Wei, Xulin Chen, Fengze Xie +3
Reinforcement learning has enabled impressive locomotion skills on articulated robots, but common policy representations remain only weakly aligned with robot physics. Generic netw…
WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems
Yuchen Wang, Jiangtao Kong, Sizhe Wei +6
Trajectory world models play a crucial role in robotic dynamics learning, planning, and control. While recent works have explored trajectory world models for diverse robotic system…
Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning
Fengze Xie, Sizhe Wei, Yue Song +2
We present a morphological-symmetry-equivariant heterogeneous graph neural network, namely MS-HGNN, for robotic dynamics learning, that integrates robotic kinematic structures and…
GaussianFormer3D: Multi-Modal Gaussian-based Semantic Occupancy Prediction with 3D Deformable Attention
Lingjun Zhao, Sizhe Wei, James Hays +1
3D semantic occupancy prediction is essential for achieving safe, reliable autonomous driving and robotic navigation. Compared to camera-only perception systems, multi-modal pipeli…
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation
Ziyan Wang, Sizhe Wei, Xiaoming Huo +1
Diffusion models have made significant advancements in recent years. However, their performance often deteriorates when trained or fine-tuned on imbalanced datasets. This degradati…