Adaptor Grammars: A framework for Bayesian non-parametric grammatical inference Mark Johnson joint work with Katherine Demuth, Michael Frank, Sharon Goldwater, Tom Griffiths and Bevan Jones

Source URL: web.science.mq.edu.au

A Bayesian Prediction Model for the U.S. Presidential Election American Politics Research Volume 37 Number 4

Source URL: electionanalytics.cs.illinois.edu

• Statistical theory
• Statistics
• Statistical forecasting
• Prior probability
• Electoral College
• Bayesian inference
• Probability

Bayesian Inference of Grammars Mark Johnson joint work with Sharon Goldwater and Tom Griffiths Microsoft Research / Brown University July 2007

Source URL: web.science.mq.edu.au

Lecture 2: Inference and Learning in Bayesian Networks • Abductive Inference in BNs

Source URL: scm.ulster.ac.uk

MCMCpack: An Evolving R Package for Bayesian Inference Andrew D. Martin Washington University St. Louis, Missouri, USA Kevin M. Quinn

Source URL: mcmcpack.berkeley.edu

Coupled Bayesian Sets Algorithm for Semi-supervised Learning and Information Extraction Saurabh Verma Baranas Hindu University, India

Source URL: rtw.ml.cmu.edu

• Statistical theory
• Bayesian statistics
• Estimation theory
• Statistical inference
• Statistical models

Recap .... Bayesian Tests .....

Source URL: genome.sph.umich.edu

• Statistics
• Logic
• Statistical theory
• Bayesian network
• Statistical inference

Improving nonparameteric Bayesian inference: experiments on unsupervised word segmentation with adaptor grammars Mark Johnson1 Sharon Goldwater2

Source URL: web.science.mq.edu.au

Bayesian Inference for Dirichlet-Multinomials and Dirichlet Processes Mark Johnson Macquarie University Sydney, Australia

Source URL: web.science.mq.edu.au

data-microscopes: Bayesian non-parametric inference made simple in Python Stephen Tu SF Python - August 20, 2014

Source URL: www.cs.berkeley.edu