Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning. - Adam Zagorecki; Mark Voortman; Marek J. Druzdzel (FLAIRS, 2006)

Insensitivity of Constraint-Based Causal Discovery Algorithms to Violations of the Assumption of Multivariate Normality. - Mark Voortman; Marek J. Druzdzel (FLAIRS, 2008)

Learning Why Things Change: The Difference-Based Causality Learner. - Mark Voortman; Denver Dash; Marek J. Druzdzel (UAI, 2010)

Learning Causal Models That Make Correct Manipulation Predictions. - Mark Voortman; Denver Dash; Marek J. Druzdzel (NIPS Causality: Objectives and Assessment, 2010)

Sequences of Mechanisms for Causal Reasoning in Artificial Intelligence. - Denver Dash; Mark Voortman; Martijn de Jongh (IJCAI, 2013)

Real-time decision making in urgent events: Modeling options for action. - Louise K. Comfort; Brian Colella; Mark Voortman; Scott Connelly; Jill L. Drury; Gary L. Klein; Wukich (ISCRAM, 2013)

Modeling women's menstrual cycles using PICI gates in Bayesian network. - Adam Zagorecki; Anna Lupinska-Dubicka; Mark Voortman; Marek J. Druzdzel (Int. J. Approx. Reason., 2016)