Bayesian Network

Casual Structural Modeling of Survey Questionnaires via a Bootstrapped Ordinal Bayesian Network Approach

Bootstrapped ordinal Bayesian network for survey questionnaires.

Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data

Graphical Dirichlet process.

Functional Bayesian Networks for Discovering Causality from Multivariate Functional Data

Functional causal discovery.

Individualized Causal Discovery with Latent Trajectory Embedded Bayesian Networks

Individualized causal discovery.

Model-Based Causal Discovery for Zero-Inflated Count Data

Zero-inflated generalized hypergeometric Bayesian networks.

Individualized Inference in Bayesian Quantile Directed Acyclic Graphical Models

Graphical Dirichlet process.

Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation

Discover causality from observation categorical data.

Ordinal Causal Discovery

Discover causality from observation ordinal categorical data with ordinal Bayesian networks.

Rejoinder to the Discussion of "Bayesian Graphical Models for Modern Biological Applications."

A review of Bayesian graphical models for biological applications.

Bayesian Graphical Models for Modern Biological Applications

A review of Bayesian graphical models for biological applications.

Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks

Zero-inflated Poisson Bayesian networks.

Bayesian Graphical Regression

A new directed acyclic graphical model that produces subject-specific and predictive graphs with theoretical guarantee.

Sparse Multi-Dimensional Graphical Models: A Unified Bayesian Framework

An array-variate directed acyclic graphical model for tensor data.

Bayesian Nonlinear Model Selection for Gene Regulatory Networks

A Bayesian directed acyclic graphical model to recover the structure of nonlinear gene regulatory networks.

Integrative Bayesian Network Analysis of Genomic Data

An integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient’s clinical outcome.