95 citations · 620 across the 56 of their papers we have counts for
6 papers · 1 filter
Prediction of Carbon Nanostructure Mechanical Properties and Role of Defects Using Machine Learning
Qi Zhao, Jordan J. Winetrout, Yanxun Xu +2
Carbon fiber and graphene-based nanostructures such as carbon nanotubes (CNTs) and defective structures have extraordinary potential as strong and lightweight materials. A longstan…
Graph skeletonization of high-dimensional point cloud data via topological method
Lucas Magee, Yusu Wang
Geometric graphs form an important family of hidden structures behind data. In this paper, we develop an efficient and robust algorithm to infer a graph skeleton of a high-dimensio…
Approximation algorithms for 1-Wasserstein distance between persistence diagrams
Samantha Chen, Yusu Wang
Recent years have witnessed a tremendous growth using topological summaries, especially the persistence diagrams (encoding the so-called persistent homology) for analyzing complex…
Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph
Chen Cai, Nikolaos Vlassis, Lucas Magee +6
We present a SE(3)-equivariant graph neural network (GNN) approach that directly predicting the formation factor and effective permeability from micro-CT images. FFT solvers are es…
Topology-Aware Segmentation Using Discrete Morse Theory
Xiaoling Hu, Yusu Wang, Li Fuxin +2
In the segmentation of fine-scale structures from natural and biomedical images, per-pixel accuracy is not the only metric of concern. Topological correctness, such as vessel conne…
Graph Coarsening with Neural Networks
Chen Cai, Dingkang Wang, Yusu Wang
As large-scale graphs become increasingly more prevalent, it poses significant computational challenges to process, extract and analyze large graph data. Graph coarsening is one po…