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UAI Workshops Program

Sunday, July 27


1. Bayesian Modeling Applications Workshop
(Workshop website:
2. Causal Inference: Learning and Prediction Workshop
(Workshop website:

Bayesian Modeling Applications Workshop (Room: 308A)

8:15am - 9:00am. Breakfast 9:00am - 9:15am. Welcome
9:15am - 10:30am. Session 1
9:15am - 9:40am – A Comparison of Two MCMC Algorithms for Hierarchical Mixture Models
Russell Almond
9:40am - 10:05am – Multi-process models -- An application for the construction of financial factor models
Kevin Keane, Jason Corso
10:05am - 10:30am – Trade-Based Asset Models for Combinatorial Prediction Markets
Wei Sun, Robin Hanson, Kathryn Laskey, Charles Twardy 10:30am - 11:00am. Coffee Break
11:00am - 12:15pm. Session 2
11:00am - 11:25am – Hydrologic Predictions using Probabilistic Relational Models
Max Metzger, Alison O'Connor, David Boutt
11:25am - 11:50am – An object-oriented dynamic Bayesian decision network model for grasslands adaptive management
Owen Woodberry, Jess Millett-Riley, Steve Sinclair, Ann Nicholson
11:50am - 12:15pm – Semantics for Improving Accuracy and Reducing Complexity in Strategic Decision Facilitation Tools
Oscar Kipersztok 12:15pm - 2:15pm. Lunch (on your own)
2:15pm - 3:30pm. Session 3
2:15pm - 2:40pm – Bayesian Network Parameter Learning using EM with Parameter Sharing
Erik Reed, Ole Mengshoel
2:40pm - 3:05pm – Using Bayesian Attack Detection Models to Drive Cyber Deception
James Jones, Kathryn Laskey
3:05pm - 3:30pm – Using Bayesian Networks to Identify and Prevent Split Purchases in Brazil
Rommel Carvalho, Leonardo Sales, Henrique Rocha, Gilson Libório Mendes 3:30pm - 4:00pm. Coffee Break
4:00pm - 5:15pm. Session 4
4:00pm - 4:25pm – Hierarchical Bayesian Survival Analysis and Projective Covariate Selection in Cardiovascular Event Risk Prediction
Tomi Peltola, Aki S. Havulinna, Veikko Salomaa, Aki Vehtari
4:25pm - 4:50pm – Dynamic Bayesian Network Modeling of Vascularization in Engineered Tissues
Caner Komurlu, Jinjian Shao, Mustafa Bilgic
4:50pm - 5:15pm – Open discussion and wrap-up

Causal Inference: Learning and Prediction Workshop (Room: 308B)

8:15am - 9:00am. Breakfast
9:00am - 10:25am. Session 1
9:00am – On causal explanations of quantum correlations
Robert Spekkens (invited talk)
9:55am – Constructing Separators and Adjustment Sets in Ancestral Graphs
Benito van der Zander, Maciej Liśkiewicz, Johannes Textor 10:30am - 11:00am. Coffee Break
11:00am - 12:10pm. Session 2
11:00am – Type-II errors of independence tests can lead to arbitrarily large errors in estimated causal effects: an illustrative example
Nicholas Cornia, Joris M. Mooij
11:35am – Estimating Causal Effects by Bounding Confounding
Philipp Geiger, Dominik Janzing, Bernhard Schölkopf
12:10pm - 2:00pm. Lunch (on your own)
2:00pm - 3:30pm. Session 3
2:00pm – Generalizability in Causal Inference
Elias Bareinboim (invited talk)
2:55pm – How Occam's Razor Provides a Neat Definition of Direct Causation
Alexander Gebharter, Gerhard Schurz 3:30pm - 4:00pm. Coffee Break
4:00pm - 5:10pm. Session 4
4:00pm – Improving Propensity Score Matching for Causal Inference on Relational Data
David Arbour, Katerina Marazopoulou, David Jensen
4:35pm – Graphical and Causal Process Models
Christopher Meek
5:10pm. End

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