BookDOI
Bayesian Nonparametrics: Subject index
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The article was published on 2010-01-01. It has received 174 citations till now.read more
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Probabilistic machine learning and artificial intelligence
TL;DR: This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.
Journal ArticleDOI
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
TL;DR: The nested Chinese restaurant process (nCRP) as discussed by the authors is a stochastic process that assigns probability distributions to ensembles of infinitely deep, infinitely branching trees, and it can be used as a prior distribution in a Bayesian nonparametric model of document collections.
Journal ArticleDOI
Philosophy and the practice of Bayesian statistics
TL;DR: The authors argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism, and examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision.
Journal ArticleDOI
Philosophy and the practice of Bayesian statistics
TL;DR: The authors argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism, and examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision.
Journal ArticleDOI
Efficient discovery of overlapping communities in massive networks
Prem Gopalan,David M. Blei +1 more
TL;DR: This paper develops a scalable approach to community detection that discovers overlapping communities in massive real-world networks based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities.