Hierarchical Bayesian Modeling with Ensemble MCMC

Source URL: astrostatistics.psu.edu

´ repulsive processes Bayesian inference for Matern (Supplementary material) Vinayak Rao∗ Department of Statistics, Purdue University, USA

Source URL: www.stat.purdue.edu

Bayesian nonparametric models for bipartite graphs Fran¸cois Caron Department of Statistics, Oxford Statistics Colloquium, Harvard University

Source URL: www.stats.ox.ac.uk

Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis Zenglin Xu, Feng Yan {XU 218, YAN 12}@ PURDUE . EDU Department of Computer Science, Purdue University, West Lafayette, INUSA

Source URL: www.cs.purdue.edu

1 Variational Bayesian Image Restoration with a Product of Spatially Weighted Total Variation Image Priors Giannis Chantas, Nikolaos Galatsanos, Rafael Molina, and Aggelos Katsaggelos

Source URL: decsai.ugr.es

• Statistics
• Statistical models
• Statistical theory
• Bayesian statistics
• Probability
• Bayesian network
• Networks
• Variational Bayesian methods

Nonparametric Bayesian Statistics: Part III Tamara Broderick ITT Career Development Assistant Professor Electrical Engineering & Computer Science MIT

Source URL: www.tamarabroderick.com

1 Bayesian Inference for Linear Dynamic Models with Dirichlet Process Mixtures F. Caron1 , M. Davy1 , A. Doucet2 , E. Duflos1 , P. Vanheeghe1 . 1 CNRS/Ecole Centrale de Lille, Villeneuve d’Ascq, France

Source URL: www.stats.ox.ac.uk

Statistica Sinica), BAYESIAN NONPARAMETRIC CONSTRUCTION OF THE FLEMING-VIOT PROCESS WITH FERTILITY SELECTION Matteo Ruggiero and Stephen G. Walker

Source URL: www.matteoruggiero.it

Infants consider both the sample and the sampling process in inductive generalization Hyowon Gweon, Joshua B. Tenenbaum, and Laura E. Schulz1 Department of Brain and Cognitive Sciences, Massachusetts Institute of Technol

Source URL: eccl.mit.edu

• Statistics
• Knowledge
• Statistical theory
• Statistical inference
• Psychometrics
• Hypothesis testing
• Survey methodology
• Sampling
• Bayesian inference
• Simple random sample
• Bayesian network
• Statistical hypothesis testing

Evidence-Specific Structures for Rich Tractable CRFs Carlos Guestrin Carnegie Mellon University

Source URL: select.cs.cmu.edu

• Graph theory
• Graphical models
• Machine learning
• Artificial intelligence
• Learning
• Statistical models
• Conditional random field
• Bayesian network
• Tree decomposition
• Treewidth
• Markov random field
• Expectationmaximization algorithm