International Society for Bayesian Analysis

The International Society for Bayesian Analysis is a professional society founded to promote the development and application of Bayesian analysis useful in the solution of theoretical and applied problems in science, industry and government. By sponsoring and organizing meetings, publishing the electronic journal Bayesian Analysis, the quarterly ISBA Bulletin and other activities ISBA provides a focal point for those interested in Bayesian analysis and its applications.

Publications

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Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper) Andrew Gelman Bayesian Analysis, Volume 1, Number 3 (2006)
Constrained Bayesian Optimization with Noisy Experiments Benjamin Letham, Brian Karrer, Guilherme Ottoni, and Eytan Bakshy Bayesian Analysis (2018)
Using Stacking to Average Bayesian Predictive Distributions (with Discussion) Yuling Yao, Aki Vehtari, Daniel Simpson, and Andrew Gelman Bayesian Analysis, Volume 13, Number 3 (2018)
Deep Learning: A Bayesian Perspective Nicholas G. Polson and Vadim Sokolov Bayesian Analysis, Volume 12, Number 4 (2017)
Flexible paleoclimate age-depth models using an autoregressive gamma process Maarten Blaauw and J. Andrés Christen Bayesian Analysis, Volume 6, Number 3 (2011)