Rating Table Tennis Players. An application of Bayesian inference. Ratings. The USATT rates all members A rating is an integer between 0 and 3000. Fan Yi Yong 2774. Example. Lee Bahlman 2045 Dell Sweeris 2080. Todd Sweeris. Old System. Example. Lee Bahlman (2045)

ByLearning Bayesian Networks from Data. Nir Friedman Daphne Koller Hebrew U. Stanford . Overview. Introduction Parameter Estimation Model Selection Structure Discovery Incomplete Data Learning from Structured Data. Qualitative part :

ByBugs. Strategy. Remember, these models are inherently complex You don’t want to make them needlessly complex Start with lm/glm Estimate in lmer Move to Bugs You can do the first two. Bayesian Inference and priors. The difficulty is in estimating the two levels of model simultaneously.

ByMore about Posterior Distributions. The process of Bayesian inference involves passing from a prior distribution to a posterior distribution. It is natural to expect that some general relations might hold between these two distributions.

Bywww.poulinhugin.com. Overview. Brief Project History Hugin Expert A/S and Bayesian Technology Discussion Poulin Automation Tool Discussion. Hugin Software?. Product maturity and optimisation produce the world ’ s fastest Bayesian inference engine

ByY=sqrt(X). sqrt(S 2 ). . 2. S 2. Sample variance and sample error. We learned recently how to determine the sample variance using the sample mean. How do we translate this to an unbiased estimate of the error on a single point?

By(Mis)understanding medical information: healthcare professionals and laymen alike. Talya Miron-Shatz, Ph.D. Center for Health and Wellbeing Princeton University Talk at the School of Public Affairs, Baruch College. Agenda. Who should understand medical information?

ByCMSC 471 Fall 2009. Class #18 – Thursday, October 29. Today’s class. Probability theory Bayesian inference From the joint distribution Using independence/factoring From sources of evidence. Bayesian Reasoning. Chapter 13. Sources of uncertainty. Uncertain inputs Missing data

ByBayesian Inference of Neural Activity and Connectivity from All-Optical Interrogation of a Neural Circuit. Ionatan J. Kuperwajs Howard Hughes Medical Institute Janelia Research Campus, Turaga Lab. Talk Outline. Problem + Dataset, VI Model Framework Recognition + Generative Models

ByConnectionism. “Frank Rosenblatt, Alan M. Turing, Connectionism, and AI” May 6, 2011 Version 4.0; 05/06/2011 John M. Casarella Proceedings of Student/Faculty Research Day Ivan G. Seidenberg School of CSIS, Pace University. Abstract.

ByIntroduction to Spatial Regression. Glen Johnson, PhD Lehman College / CUNY School of Public Health glen.johnson@lehman.cuny.edu. Typical scenario: Have a health outcome and covariables aggregated at a common geographic level, such as counties, census tracts, ZIP codes …

ByLecture 16: Unsupervised Learning from Text. Padhraic Smyth Department of Computer Science University of California, Irvine . Outline. General aspects of text mining Named-entity extraction, question-answering systems, etc Unsupervised learning from text documents Motivation

ByMulti-Model Data Fusion for Hydrological Forecasting. Linda See 1 and Bob Abrahart 2 1 Centre for Computational Geography, University of Leeds, UK 2 School of Earth and Environmental Sciences, University of Greenwich, UK. What is Data Fusion?.

ByToday’s class. Probability theory Bayesian inference From the joint distribution Using independence/factoring From sources of evidence. Bayesian Reasoning. Chapter 13. Sources of uncertainty. Uncertain inputs Missing data Noisy data Uncertain knowledge

ByNonparametric hidden Markov models. Jurgen Van Gael and Zoubin Ghahramani. Introduction. HM models: time series with discrete hidden states Infinite HM models ( iHMM ): nonparametric Bayesian approach Equivalence between Polya urn and HDP interpretations for iHMM

ByIntelligent data analysis B iomarker discovery II. Peter Antal antal@mit.bme.hu. Overview. Biomarkers The Bayesian statistical approach Partial multivariate analysis Marginalization, sub-, sup-relevance Frontlines Causal , confounded extension Multitarget (multidimensional)extension

ByDepartment of Electrical and Computer Engineering. Zhu Han Department of Electrical and Computer Engineering University of Houston. Thanks to Nam Nguyen , Guanbo Zheng , and Dr. Rong Zheng. Bayesian Nonparametric Classification and Applications. Bayesian Nonparametric Classification.

ByTomas Radivoyevitch · David G. Hoel . Biologically-based risk estimation for radiation-induced chronic myeloid leukemia. Radiat Environ Biophys (2000) 39:153–159 Suppose we have vectors of model parameters θ and observed data X . Bayes theorem

BySwets et al (1961). Key ideas. continuity in stimulus-induced mental states variability in these states sensitivity (d’) role of prior probability and payoffs bias, criterion… Bayesian inference n ormative/optimal model, ideal observer. Your questions.

ByFusing Multiple Video Sensors for Surveillance. By: Lauro Snidaro Ingrid Visentini Gian Luca Foresti. Presented By: Sushma Ajjampur Jagadeesh. Introduction. Why surveillance system? What is video surveillance system? Fundamental issues with surveillance system.

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