9:00  9:30 p.m.
REGISTRATION  2nd Floor, Fields Institute
9:30  11:00 p.m.
David Heckerman
DecisionTheoretic Foundations for Causal Reasoning
2:00  4:00 p.m.
COXETER LECTURE SERIES
Greg Cooper
Causal Discovery from a Mixture of Experimental and Observational Data

9:00  11:00 a.m.
Paolo Guidici
MCMC Methods for Structural Learning in Graphical Models
2:00  4:00 p.m.
Steffen Lauritzen
Perfect Simulation for Model Averaging
 9:00  10:00 a.m.
Thomas Richardson
Causal Inference from Observational Data via Conditional Independence
10:15  11:00 a.m.
David Heckerman
A Bayesian Approach to Learning Causal Networks
2:00  3:00
Jie Cheng
3:30  5:30 p.m.
Glenn Shafer
SEWALL WRIGHT LECTURE The Language of Causality

9:00  10:00 p.m.
Johan Andersen
The EM Algorithm for Bayesian Networks with Mixed DiscreteGaussian Variables
10:00  11:00 p.m.
Steffen Lauritzen
The ME Algorithm for Maximizing a Conditional Likelihood Function
11:15  12:30 p.m.
Brendan Frey Inference and Learning in Bayesian Networks
12:30  1:30 p.m.
David Heckerman
(Room 230) Causal Discovery from NonExperimental Data
3:30  5:30 p.m.
Brendan Frey
Iterative Decoding of ErrorCorrecting Codes (turbodecoding) 