3 papers
stat.ME2024
Flexible Bayesian Nonparametric Product Mixtures for Multi-scale Functional Clustering
Tsung-Hung Yao, Suprateek Kundu
There is a rich literature on clustering functional data with applications to time-series modeling, trajectory data, and even spatio-temporal applications. However, existing method…
stat.ME2024
Geometry-driven Bayesian Inference for Ultrametric Covariance Matrices
Tsung-Hung Yao, Zhenke Wu, Karthik Bharath +1
Ultrametric matrices are a class of covariance matrices that arise in latent tree models. As a parameter space in a statistical model, the set of ultrametric matrices is neither co…
stat.ME2023
Robust Bayesian Graphical Regression Models for Assessing Tumor Heterogeneity in Proteomic Networks
Tsung-Hung Yao, Yang Ni, Anindya Bhadra +2
Graphical models are powerful tools to investigate complex dependency structures in high-throughput datasets. However, most existing graphical models make one of the two canonical…