32 citations · 46 across the 18 of their papers we have counts for
5 papers · 1 filter
The Promises of Parallel Outcomes
Ying Zhou, Dingke Tang, Dehan Kong +1
A key challenge in causal inference from observational studies is the identification and estimation of causal effects in the presence of unmeasured confounding. In this paper, we i…
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…
Ultra-high Dimensional Variable Selection for Doubly Robust Causal Inference
Dingke Tang, Dehan Kong, Wenliang Pan +1
Causal inference has been increasingly reliant on observational studies with rich covariate information. To build tractable causal procedures, such as the doubly robust estimators,…
Covariance Estimation for Matrix-valued Data
Yichi Zhang, Weining Shen, Dehan Kong
Covariance estimation for matrix-valued data has received an increasing interest in applications. Unlike previous works that rely heavily on matrix normal distribution assumption a…