PPT-Bayesian Networks, Influence Diagrams,

and Games in Simulation Metamodeling Jirka Poropudas MSc Aalto University School of Science and Technology Systems Analysis Laboratory httpwwwsaltkkfien jirkaporopudastkkfi . Bayesian Network Motivation. We want a representation and reasoning system that is based on conditional . independence. Compact yet expressive representation. Efficient reasoning procedures. Bayesian Networks are such a representation. Read R&N Ch. 14.1-14.2. Next lecture: Read R&N 18.1-18.4. You will be expected to know. Basic concepts and vocabulary of Bayesian networks.. Nodes represent random variables.. Directed arcs represent (informally) direct influences.. Author: David Heckerman. . Presented By:. Yan Zhang - 2006. Jeremy Gould – 2013. 1. Outline. Bayesian Approach. Bayesian vs. classical probability methods. Examples. Bayesian Network. Structure. Author: David Heckerman. . Presented By:. Yan Zhang - 2006. Jeremy Gould – 2013. Chip Galusha -2014. 1. Outline. Bayesian Approach. Bayesian vs. classical probability methods. Bayes. . Theorm. Bayes Net Perspectives on Causation and Causal Inference. 1. Example Problems. Genetic regulatory networks. Yeast – ~5000 genes, ~2,500,000 potential edges. 2. A gene regulatory network in mouse embryonic stem cells http://www.pnas.org/content/104/42/16438/F3.expansion.html. Author: David Heckerman. . Presented By:. Yan Zhang - 2006. Jeremy Gould – 2013. 1. Outline. Bayesian Approach. Bayesian vs. classical probability methods. Examples. Bayesian Network. Structure. Author: David Heckerman. . Presented By:. Yan Zhang - 2006. Jeremy Gould – 2013. Chip Galusha -2014. 1. Outline. Bayesian Approach. Bayesian vs. classical probability methods. Bayes. . Theorm. Model representation and analysis. Presented by:. Ayushi Jain Rahul . Bobhate. Natasha Mandal . Ankur. . Sachdeva. Dung T. Nguyen, . Huiyuan. Zhang, . Soham. Das, My T. Thai, Thang N. . Dinh. or. How to combine data, evidence, opinion and guesstimates to make decisions. Information Technology. Professor Ann Nicholson. Faculty of Information Technology. Monash University . (Melbourne, Australia). Units. IEOR 8100.003 Final Project. 9. th. May 2012. Daniel Guetta. Joint work with Carri Chan. This talk. Hospitals. Bayesian Networks. Data!. Modified EM Algorithm. First results. Instrumental variables. of Bayesian Network Diagrams. Dr. . Kamaran. . Fathulla. University of Essex. International Academy. kamaran@essex.ac.uk. June 2011. Clay Tablet map from Ga-Sur, Kirkuk, 2,500 B.C.. Some 2500 years ago people have used clay tablets to express boundaries, groupings, and routes. Cognitive Science. Current Problem:. . How do children learn and how do they get it right?. Connectionists and Associationists. Associationism:. . maintains that all knowledge is represented in terms of associations between ideas, that complex ideas are built up from combinations of more primitive ideas, which, in accordance with empiricist philosophy, are ultimately derived from the senses. . Part III: Models. Part 1: Introduction & Theory. History & Big Picture. Network Relevance to Health Research. Network Theory. Connections . & . Positions. Part 2: Points & Lines. Network data. IEOR 8100.003 Final Project. 9. th. May 2012. Daniel Guetta. Joint work with Carri Chan. This talk. Hospitals. Bayesian Networks. Data!. Modified EM Algorithm. First results. Instrumental variables.