Efficient Sampling and Structure Learning of Bayesian Networks

Links between psychotic and neurotic symptoms in the general population: an analysis of longitudinal British National Survey data using Directed Acyclic Graphs

(2018) J. Kuipers et al.   PSYCHOLOGICAL MEDICINE

High-dimensional consistency in score-based and hybrid structure learning

(2018) Preetam Nandy et al.   ANNALS OF STATISTICS

Mutational interactions define novel cancer subgroups

(2018) Jack Kuipers et al.   Nature Communications

Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity

(2017) James Cussens et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

Partition MCMC for Inference on Acyclic Digraphs

(2017) Jack Kuipers et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

A BIRTH AND DEATH PROCESS FOR BAYESIAN NETWORK STRUCTURE INFERENCE

(2017) Dale Jennings et al.   PROBABILITY IN THE ENGINEERING AND INFORMATIONAL SCIENCES

Using Directed Acyclic Graphs in Epidemiological Research in Psychosis: An Analysis of the Role of Bullying in Psychosis

(2017) Giusi Moffa et al.   SCHIZOPHRENIA BULLETIN

Causal Inference Using Graphical Models with theRPackagepcalg

(2015) Markus Kalisch et al.   Journal of Statistical Software

Addendum on the scoring of Gaussian directed acyclic graphical models

(2014) Jack Kuipers et al.   ANNALS OF STATISTICS

Geometry of the faithfulness assumption in causal inference

(2013) Caroline Uhler et al.   ANNALS OF STATISTICS

Uniform random generation of large acyclic digraphs

(2013) Jack Kuipers et al.   STATISTICS AND COMPUTING

Estimating high-dimensional intervention effects from observational data

(2009) Marloes H. Maathuis et al.   ANNALS OF STATISTICS

Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move

(2008) Marco Grzegorczyk et al.   MACHINE LEARNING