16 citations · 18 across the 9 of their papers we have counts for
10 papers
Topology-Preserving Neural Operator Learning via Hodge Decomposition
Dongzhe Zheng, Tao Zhong, Christine Allen-Blanchette
In this paper, we study solution operators of physical field equations on geometric meshes from a function-space perspective. We reveal that Hodge orthogonality fundamentally resol…
HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts
Tao Zhong, Dongzhe Zheng, Christine Allen-Blanchette
Sparse Mixture-of-Experts (MoE) layers route tokens through a handful of experts, and learning-free compression of these layers reduces inference cost without retraining. A subtle…
Neural Fields for NV-Center Inverse Sensing
Zhixuan Zhao, Tao Zhong, Yixun Hu +2
Inverse problems in scientific sensing are often solved with either hand-designed regularizers or supervised networks trained on simulated labels, yet both can fail when the forwar…
Neural Field Thermal Tomography: A Differentiable Physics Framework for Non-Destructive Evaluation
Tao Zhong, Yixun Hu, Dongzhe Zheng +2
Inverse problems for stiff parabolic partial differential equations (PDEs), such as the inverse heat conduction problem (IHCP), are severely ill-posed: the forward map rapidly damp…
Local-Canonicalization Equivariant Graph Neural Networks for Sample-Efficient and Generalizable Swarm Robot Control
Keqin Wang, Tao Zhong, David Chang +1
Multi-agent reinforcement learning (MARL) policies for swarm control often learn inefficiently and generalize poorly across coordinate frames, team sizes, and agent roles. We intro…
Grasp2Grasp: Vision-Based Dexterous Grasp Translation via Schrödinger Bridges
Tao Zhong, Jonah Buchanan, Christine Allen-Blanchette
We propose a new approach to vision-based dexterous grasp translation, which aims to transfer grasp intent across robotic hands with differing morphologies. Given a visual observat…
GAGrasp: Geometric Algebra Diffusion for Dexterous Grasping
Tao Zhong, Christine Allen-Blanchette
We propose GAGrasp, a novel framework for dexterous grasp generation that leverages geometric algebra representations to enforce equivariance to SE(3) transformations. By encoding…
Adapting to Distribution Shift by Visual Domain Prompt Generation
Zhixiang Chi, Li Gu, Tao Zhong +4
In this paper, we aim to adapt a model at test-time using a few unlabeled data to address distribution shifts. To tackle the challenges of extracting domain knowledge from a limite…
Fast-Grasp'D: Dexterous Multi-finger Grasp Generation Through Differentiable Simulation
Dylan Turpin, Tao Zhong, Shutong Zhang +8
Multi-finger grasping relies on high quality training data, which is hard to obtain: human data is hard to transfer and synthetic data relies on simplifying assumptions that reduce…
Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts
Tao Zhong, Zhixiang Chi, Li Gu +3
In this paper, we tackle the problem of domain shift. Most existing methods perform training on multiple source domains using a single model, and the same trained model is used on…