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Bayesian methods in cosmology

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RNTW01 - Rich and Nonlinear Tomography (RNT) in Radar, Astronomy and Geophysics

Bayesian inference methods are widely used to analyse observations in cosmology, but they can be extremely computationally demanding. Recent work in this area has focussed on developing new methods for greatly accelerating such analyses, in particular by using nested sampling and machine learning methods. I will give a brief outline of these approaches, which are generic in nature, and illustrate their use in a cosmological case study.

This talk is part of the Isaac Newton Institute Seminar Series series.

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