8 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…
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…
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…