1 citations · 2 across the 3 of their papers we have counts for
7 papers
Multivariate functional responses low rank regression with an application to brain imaging data
Xiucai Ding, Dengdeng Yu, Zhengwu Zhang +1
We propose a multivariate functional responses low rank regression model with possible high dimensional functional responses and scalar covariates. By expanding the slope functions…
Federated Learning for Computational Pathology on Gigapixel Whole Slide Images
Ming Y. Lu, Dehan Kong, Jana Lipkova +5
Deep Learning-based computational pathology algorithms have demonstrated profound ability to excel in a wide array of tasks that range from characterization of well known morpholog…
Nonparametric principal subspace regression
Mark Koudstaal, Dengdeng Yu, Dehan Kong +1
In scientific applications, multivariate observations often come in tandem with temporal or spatial covariates, with which the underlying signals vary smoothly. The standard approa…
Modeling Symmetric Positive Definite Matrices with An Application to Functional Brain Connectivity
Zhenhua Lin, Dehan Kong, Qiang Sun
In neuroscience, functional brain connectivity describes the connectivity between brain regions that share functional properties. Neuroscientists often characterize it by a time se…
Identifiability of causal effects with multiple causes and a binary outcome
Dehan Kong, Shu Yang, Linbo Wang
Unobserved confounding presents a major threat to causal inference from observational studies. Recently, several authors suggest that this problem may be overcome in a shared confo…
Nonparametric Matrix Response Regression with Application to Brain Imaging Data Analysis
Wei Hu, Tianyu Pan, Dehan Kong +1
With the rapid growth of neuroimaging technologies, a great effort has been dedicated recently to investigate the dynamic changes in brain activity. Examples include time course ca…