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Daning Huang

2 accepted papers

2025

Learning vector fields of differential equations on manifolds with geometrically constrained operator-valued kernels

ICLR 2025spotlight

We address the problem of learning ordinary differential equations (ODEs) on manifolds. Existing machine learning methods, particularly those using neural networks, often struggle with high computational demands. To overcome this issue, we introduce a geometrically constrained operator-valued kernel…

Cited by 0SourcePDFScholar
2023

PyPose: A Library for Robot Learning With Physics-Based Optimization

CVPR 2023poster

Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physics-based optimization generalizes better, but it does not perform as well in complicated tasks due to the lack of high-le…