4 papers
BVSIMC: Bayesian Variable Selection-Guided Inductive Matrix Completion for Improved and Interpretable Drug Discovery
Sijian Fan, Liyan Xiong, Dayuan Wang +2
Recent advances in drug discovery have demonstrated that incorporating side information (e.g., chemical properties about drugs and genomic information about diseases) often greatly…
BiSSLB: Binary Spike-and-Slab Lasso Biclustering
Sijian Fan, Ray Bai
Biclustering is a powerful unsupervised learning technique for simultaneously identifying coherent subsets of rows and columns in a data matrix, thus revealing local patterns that…
Sparse high-dimensional linear mixed modeling with a partitioned empirical Bayes ECM algorithm
Anja Zgodic, Ray Bai, Jiajia Zhang +2
High-dimensional longitudinal data is increasingly used in a wide range of scientific studies. To properly account for dependence between longitudinal observations, statistical met…
Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regression
Anja Zgodic, Ray Bai, Jiajia Zhang +3
Sparse linear regression methods for high-dimensional data commonly assume that residuals have constant variance, which can be violated in practice. For example, Aphasia Quotient (…