BayesiaLab User Conference, Sep 16-24, UCLA
Research practitioners from leading organizations will gather at UCLA for the only event dedicated to applied research and analytics with Bayesian networks and BayesiaLab. Pre-conference program includes courses on BayesiaLab and Causal Inference with Graphical Models.
2nd Annual BayesiaLab User Conference, Sept 16-24, 2014 - University of California, Los Angeles
Research practitioners from leading organizations will join us for this year's BayesiaLab User Conference, the only event dedicated to applied research and analytics with Bayesian networks and BayesiaLab. Experts will share innovative applications of Bayesian networks in a wide range of courses and case study presentations.
- September 16-18, 9am - 5pm
3-Day Introductory BayesiaLab Course, Instructor: Dr. Lionel Jouffe
Learn the foundations of Bayesian Networks and how to use them as a state-of-the-art research framework with the BayesiaLab software platform. With BayesiaLab, you can leverage recent advances in artificial intelligence for your applied research and analytics projects. Learn More & Register
- September 19-20, 9am - 4pm
2-Day Course: Causal Inference with Graphical Models, Instructor: Felix Elwert, Ph.D.
Causal Inference with Graphical Models offers an applied introduction to directed acyclic graphs (DAGs) for causal inference from observational data. Topics include non-parametric identification by adjustment; d-separation; the difference between overcontrol bias, confounding bias, and selection bias; covariate selection in observational research; causal assumptions in regression; instrumental variables; and recent developments in causal mediation. Learn More & Register
- September 21-23, 9am - 5pm
3-Day Advanced BayesiaLab Course, Instructor: Dr. Lionel Jouffe
Take your BayesiaLab certification to the next level by joining the advanced BayesiaLab course in Los Angeles. Completing this course takes you to the leading edge of applied research with Bayesian Networks.Learn More & Register
Main Conference Program
- Day 1: September 23, 6:00pm - 8:00pm
Opening Session with Keynote & Welcome Reception
Learn More & Register (Free Registration)
Keynote Speaker: Judea Pearl, Ph.D.
From Bayesian Networks to Causal and Counterfactual Reasoning
The development of Bayesian Networks, so people tell me, marked a turning point in the way uncertainty is handled in computer systems. For me, this development was a stepping stone towards a more profound transition, from reasoning about beliefs to reasoning about causal and counterfactual relationships.
In this talk, I will survey the milestones of this journey, and summarize the practical and conceptual problems that we can solve today and could not address two decades ago.
- Day 2: September 24, 7:45am - 5:45pm
Main Conference Sessions & Presentations
Researchers from the following organization will present: Rotman Business School - University of Toronto, GfK, Dell, Booz Allen Hamilton, Omnis, ExxonMobil, U.S. Army, Lieberman Research Worldwide, Geisinger Health System, Omegawave.
Learn More & Register ($299)
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