2 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Combinatorial Network-Based Manifold Topological Deep Learning for Image Analysis
Alice Wachira, Xiang Liu, Zhe Su +3
Medical image analysis remains fundamentally challenging because of the intricate geometric and topological structures present in medical data. Conventional convolutional neural ne…
Weighted Hodge Laplacians on Manifolds with Boundary
Zhe Su, Yiying Tong, Guo-Wei Wei
The spectrum of the Hodge Laplacian on differential manifolds encodes rich topological and geometric information and thus provides a powerful tool for analyzing data on manifolds.…
Persistent Manifold Learning of Protein Properties
Xingjian Xu, Zhe Su, Guo-Wei Wei +1
Predicting how tightly two biomolecules bind remains a major challenge, in part because different interaction classes present dissimilar interfaces, from compact metal-coordinated…
A vector field induced de Rham-Hodge theory on manifolds
Zhe Su
We introduce a de Rham-Hodge framework induced by a vector field on a compact, oriented smooth manifold. Using a vector field induced bundle isomorphism on differential forms, we d…