Bayesian Inference

Bayesian model comparison for simulation-based inference
Comparison of appropriate models to describe observational data is a fundamental task of science. The Bayesian model evidence, or …
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DarkMappy
Scalable mapping of the dark universe
Feb 22, 2022
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DarkMappy
Machine learning assisted Bayesian model comparison: learnt harmonic mean estimator
We resurrect the infamous harmonic mean estimator for computing the marginal likelihood (Bayesian evidence) and solve its problematic …
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Sparse Bayesian mass-mapping with uncertainties: hypothesis testing of structure
A crucial aspect of mass mapping, via weak lensing, is quantification of the uncertainty introduced during the reconstruction process. …
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Bayesian variational regularisation on the ball
We develop variational regularisation methods which leverage sparsity-promoting priors to solve severely ill posed inverse problems …
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Sparse image reconstruction on the sphere: a general approach with uncertainty quantification
Inverse problems defined naturally on the sphere are becoming increasingly of interest. In this article we provide a general framework …
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Sparse Bayesian mass-mapping with uncertainties: Full sky observations on the celestial sphere
To date weak gravitational lensing surveys have typically been restricted to small fields of view, such that the flat-sky approximation …
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Sparse Bayesian mass-mapping with uncertainties: local credible intervals
Until recently, mass-mapping techniques for weak gravitational lensing convergence reconstruction have lacked a principled statistical …
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Sparse Bayesian mass-mapping with uncertainties: peak statistics and feature locations
Weak lensing convergence maps – upon which higher order statistics can be calculated – can be recovered from observations of the shear …
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Sparse Bayesian mass-mapping with uncertainties
Mass-mapping via weak gravitational lensing has until recently lacked principled statistical consideration of uncertainties introduced …
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