1 citations · 1 across the 4 of their papers we have counts for
4 papers
Efficient prior sensitivity analysis for Bayesian model comparison
Zixiao Hu, Jason D. McEwen
Bayesian model comparison implements Occam's razor through its sensitivity to the prior. However, prior-dependence makes it important to assess the influence of plausible alternati…
Savage-Dickey density ratio estimation with normalizing flows for Bayesian model comparison
Kiyam Lin, Alicja Polanska, Davide Piras +2
A core motivation of science is to evaluate which scientific model best explains observed data. Bayesian model comparison provides a principled statistical approach to comparing sc…
Simulation-based inference with scattering representations: scattering is all you need
Kiyam Lin, Benjamin Joachimi, Jason D. McEwen
We demonstrate the successful use of scattering representations without further compression for simulation-based inference (SBI) with images (i.e. field-level), illustrated with a…
Field-level cosmological model selection: field-level simulation-based inference for Stage IV cosmic shear can distinguish dynamical dark energy
A. Spurio Mancini, K. Lin, J. D. McEwen
We present a framework that for the first time allows Bayesian model comparison to be performed for field-level inference of cosmological models. We achieve this by taking a simula…