3 citations · 8 across the 5 of their papers we have counts for
5 papers
Robust High-Dimensional Covariate-Assisted Network Modeling
Peng Zhao, Yabo Niu
Modern network data analysis often involves analyzing network structures alongside covariate features to gain deeper insights into underlying patterns. However, traditional covaria…
Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data
Yabo Niu, Yang Ni, Debdeep Pati +1
In a traditional Gaussian graphical model, data homogeneity is routinely assumed with no extra variables affecting the conditional independence. In modern genomic datasets, there i…
Off-Policy Evaluation Using Information Borrowing and Context-Based Switching
Sutanoy Dasgupta, Yabo Niu, Kishan Panaganti +3
We consider the off-policy evaluation (OPE) problem in contextual bandits, where the goal is to estimate the value of a target policy using the data collected by a logging policy.…
Bayesian Variable Selection in Multivariate Nonlinear Regression with Graph Structures
Yabo Niu, Nilabja Guha, Debkumar De +3
Gaussian graphical models (GGMs) are well-established tools for probabilistic exploration of dependence structures using precision matrices. We develop a Bayesian method to incorpo…
Bayesian Graph Selection Consistency Under Model Misspecification
Yabo Niu, Debdeep Pati, Bani Mallick
Gaussian graphical models are a popular tool to learn the dependence structure in the form of a graph among variables of interest. Bayesian methods have gained in popularity in the…