147 citations · 208 across the 22 of their papers we have counts for
22 papers
Bayesian Methods in Tensor Analysis
Yiyao Shi, Weining Shen
Tensors, also known as multidimensional arrays, are useful data structures in machine learning and statistics. In recent years, Bayesian methods have emerged as a popular direction…
Precision education: A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data
Tianyu Pan, Weining Shen, Clintin P. Davis-Stober +1
We propose a novel nonparametric Bayesian IRT model in this paper by introducing the clustering effect at question level and further assume heterogeneity at examinee level under ea…
Multidimensional heterogeneity learning for count value tensor data with applications to field goal attempt analysis of NBA players
Guanyu Hu, Yishu Xue, Weining Shen
We propose a multidimensional tensor clustering approach for studying how professional basketball players' shooting patterns vary over court locations and game time. Unlike most ex…
Nonparametric tests for treatment effect heterogeneity in observational studies
Maozhu Dai, Weining Shen, Hal S. Stern
We consider the problem of testing for treatment effect heterogeneity in observational studies, and propose a nonparametric test based on multisample U-statistics. To account for p…
Addressing patient heterogeneity in disease predictive model development
Xu Gao, Weining Shen, Jing Ning +2
This paper addresses patient heterogeneity associated with prediction problems in biomedical applications. We propose a systematic hypothesis testing approach to determine the exis…
Graph signal denoising using -shrinkage priors
Sayantan Banerjee, Weining Shen
We study the graph signal denoising problem by estimating a piecewise constant signal over an undirected graph. We propose a new Bayesian approach that first converts a general gra…