David Dunson develops Bayesian inference and statistical machine learning for complex data. His research seeks lower-dimensional structure in observations such as networks, functions and biological measurements, with applications in ecology, neuroscience and environmental health.[ref]
A model may represent many dependent measurements through a smaller set of latent quantities, then carry uncertainty about those quantities into predictions. Dunson's work couples flexible modelling with algorithms for Bayesian inference and uncertainty quantification. He is also a coauthor of Bayesian Data Analysis by Andrew Gelman and others.[ref]
Bayesian Data Analysis by Andrew Gelman and others. Verified third-edition coauthor list
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David Dunson is a name that could refer to different individuals, depending on the context. One notable figure is David Dunson, a professor of statistical science known for his work in Bayesian statistics and data analysis. He has contributed significantly to various fields, including biostatistics and machine learning.