16 citations · 23 across the 7 of their papers we have counts for
7 papers
Deep Representation Learning For Multimodal Brain Networks
Wen Zhang, Liang Zhan, Paul Thompson +1
Applying network science approaches to investigate the functions and anatomy of the human brain is prevalent in modern medical imaging analysis. Due to the complex network topology…
Variational Wasserstein Barycenters for Geometric Clustering
Liang Mi
We propose to compute Wasserstein barycenters (WBs) by solving for Monge maps with variational principle. We discuss the metric properties of WBs and explore their connections, esp…
Geometric Brain Surface Network For Brain Cortical Parcellation
Wen Zhang, Yalin Wang
A large number of surface-based analyses on brain imaging data adopt some specific brain atlases to better assess structural and functional changes in one or more brain regions. In…
Graph Neural Networks for User Identity Linkage
Wen Zhang, Kai Shu, Huan Liu +1
The increasing popularity and diversity of social media sites has encouraged more and more people to participate in multiple online social networks to enjoy their services. Each us…
Regularized Wasserstein Means for Aligning Distributional Data
Liang Mi, Wen Zhang, Yalin Wang
We propose to align distributional data from the perspective of Wasserstein means. We raise the problem of regularizing Wasserstein means and propose several terms tailored to tack…
Brain Morphometry Analysis with Surface Foliation Theory
Chengfeng Wen, Na Lei, Ming Ma +4
Brain morphometry study plays a fundamental role in neuroimaging research. In this work, we propose a novel method for brain surface morphometry analysis based on surface foliation…
Variational Wasserstein Clustering
Liang Mi, Wen Zhang, Xianfeng Gu +1
We propose a new clustering method based on optimal transportation. We solve optimal transportation with variational principles, and investigate the use of power diagrams as transp…