4 citations · 4 across the 6 of their papers we have counts for
8 papers
RiVaT-Fuse: Reliability-Calibrated Variational Tensor Fusion with Matrix-Valued Trust for Multimodal Prediction under Modality Uncertainty
Yingfan Xu, Tieming Liu, Ye Liang +1
Multimodal prediction from images and structured metadata requires integrating complementary evidence whose reliability can vary across samples and latent directions. A single conf…
DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction
Yingfan Xu, Tieming Liu, Ye Liang
Pretrained diabetic retinopathy (DR) prediction models differ in their input fields, serialization formats, preprocessing requirements, and output semantics. Making these models ac…
Cluster-induced target shift and synthetic approximation for high-dimensional clustered data
Shangyuan Ye, Cong Zhang, Ying Chen +2
In high-dimensional clustered data, covariates whose distributions differ across clusters can act as proxies for unobserved cluster effects. We show that the marginal-model LASSO i…
High-dimensional Statistical Inference and Variable Selection Using Sufficient Dimension Association
Shangyuan Ye, Shauna Rakshe, Ye Liang
Simultaneous variable selection and statistical inference is challenging in high-dimensional data analysis. Most existing post-selection inference methods require explicitly specif…
The Inuence of Misspecified Covariance on False Discovery Control when Using Posterior Probabilities
Ye Liang, Joshua D. Habiger, Xiaoyi Min
This paper focuses on the influence of a misspecified covariance structure on false discovery rate for the large scale multiple testing problem. Specifically, we evaluate the influ…
Orthogonal Series Density Estimation for Complex Surveys
Shangyuan Ye, Ye Liang, Ibrahim A. Ahmad
We propose an orthogonal series density estimator for complex surveys, where samples are neither independent nor identically distributed. The proposed estimator is proved to be des…
Bayesian Nonparametric Inference for Panel Count Data with an Informative Observation Process
Ye Liang, Yang Li, Bin Zhang
In this paper, the panel count data analysis for recurrent events is considered. Such analysis is useful for studying tumor or infection recurrences in both clinical trial and obse…
Graph-based Multivariate Conditional Autoregressive Models
Ye Liang
The conditional autoregressive model is a routinely used statistical model for areal data that arise from, for instances, epidemiological, socio-economic or ecological studies. Var…