'Markov chain monte carlo' diaporamas de présentation

Network Tomography

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Making the Most of Process Information via Multiscale and Bayesian Methods

Making the Most of Process Information via Multiscale and Bayesian Methods Bhavik R. Bakshi Department of Chemical Engineering Ohio State University Columbus, OH 43210 CPACT Conference, Edinburgh, April 25-26, 2002 Overview of Research Group

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Gibbs sampling for motif finding in biological sequences

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a tutorial on Markov Chain Monte Carlo (MCMC)

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Bioinformatics ApS

Bioinformatics ApS. Bioinformatics ApS. Founded in February 2002 with investment from Biovision Founders: Staff working at the Bioinformatics Research Center, Aarhus University Employees: 2 software developers. Founders.

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Understanding Science Through the Lens of Computation

Understanding Science Through the Lens of Computation. Richard Karp Visit Day 2008. The Computational Lens.

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Server-based Characterization and Inference of Internet Performance

Server-based Characterization and Inference of Internet Performance. Venkat Padmanabhan Lili Qiu Helen Wang Microsoft Research UCLA/IPAM Workshop March 2002. Outline. Overview Server-based characterization of performance Server-based inference of performance Passive Network Tomography

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Learning Energy-Based Models of High-Dimensional Data

Learning Energy-Based Models of High-Dimensional Data. Geoffrey Hinton Max Welling Yee-Whye Teh Simon Osindero www.cs.toronto.edu/~hinton/EnergyBasedModelsweb.htm. Discovering causal structure as a goal for unsupervised learning.

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Deciding, Estimating, Computing, Checking

Deciding, Estimating, Computing, Checking. How are Bayesian posteriors used, computed and validated?. Fundamentalist Bayes: The posterior is ALL knowledge you have about the state.

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Lower resolution X-ray spectroscopy

Lower resolution X-ray spectroscopy. Keith Arnaud NASA Goddard University of Maryland. Practical X-ray spectroscopy. Most X-ray spectra are of moderate or low resolution (eg Chandra ACIS or XMM-Newton EPIC). However, the spectra generally cover a bandpass of more than 1.5 decades in energy.

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Econ 6038: Lecture Seven Economic Evaluation of healthcare: an introduction

Econ 6038: Lecture Seven Economic Evaluation of healthcare: an introduction Raymond Yeung http://web.hku.hk/ ~rytyeung 7 November 2005 Ask yourself the following questions What are the possible economic logic behind the merge? What are the parameters you need to assess the merging proposal?

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Expectation-Maximization & Belief Propagation

Expectation-Maximization & Belief Propagation. Alan Yuille Dept. Statistics UCLA. 1. Chair. Goal of this Talk. The goal is to introduce the Expectation-Maximization (EM) and Belief Propagation (BP) algorithms.

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Markov Chain Monte Carlo

Markov Chain Monte Carlo. Prof. David Page transcribed by Matthew G. Lee. Markov Chain. A Markov chain includes A set of states A set of associated transition probabilities

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Modelling Healthcare Associated Infections: A case study in MRSA .

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Multiple Imputation

Multiple Imputation. Julia Kozlitina Steve Robertson April 26, 2006. Outline. Multiple Imputation (MI) How to impute (i.e. how to fill in values) How to analyze and draw inferences How many times to impute Alternatives to MI Applications Software. Multiple Imputation -.

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A Statistical Model for Attributing Human Salmonellosis to Meat, Poultry, and Eggs

A Statistical Model for Attributing Human Salmonellosis to Meat, Poultry, and Eggs. Chuanfa Guo, PhD Food Safety and Inspection Service on behalf of the FoodNet Attribution Working Group Modeling Subgroup Food Safety Summit Attributing Illness to Food April 5, 2007.

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Introduction to Belief Propagation and its Generalizations.

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Outline of the Topics Covered in the Machine Learning Interface Course : (see full outline for more detail)

Outline of the Topics Covered in the Machine Learning Interface Course : (see full outline for more detail). Marc Sobel. Stat 9180: Topics for the interface between Statistics, Statistical Learning, Machine Learning, Data Mining, and Computer Vision

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Results: Phylogenetic analyses: MP and MCMC resolved the same major clades. Xerus erythropus is basal to the remain

Evolution of the African ground squirrel genus Xerus : Phylogenetic and phylogeographic patterns reflect the influence of climate change Matthew D. Herron, Christopher L. Parkinson and Jane M. Waterman Department of Biology, University of Central Florida. Results: Phylogenetic analyses:

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