Introduces Gaussian Process eigenmodes to unify statistical and systematic template uncertainties, replacing per-bin factors with truncated leading modes while containing Barlow-Beeston as a limiting case.
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Emulator-assisted Bayesian inference of an extended Skyrme EDF, jointly constrained by nuclear observables, ab initio calculations, and NICER data, produces posteriors yielding consistent neutron star crust and core properties with a provided multivariate Gaussian for bulk nuclear matter parameters.
Latent-f and latent-H Gaussian process reconstructions from OHD data both yield f(z), w(z), and Om(z) consistent with Lambda-CDM, with no strong predictive preference and small prior-dependent residuals mainly at high redshift.
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Gaussian Process Eigenmodes for Statistical and Systematic Uncertainties in Template Fits
Introduces Gaussian Process eigenmodes to unify statistical and systematic template uncertainties, replacing per-bin factors with truncated leading modes while containing Barlow-Beeston as a limiting case.
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Emulator-Assisted Nuclear DFT Inference and Its Consequences for the Structure of Neutron Stars
Emulator-assisted Bayesian inference of an extended Skyrme EDF, jointly constrained by nuclear observables, ab initio calculations, and NICER data, produces posteriors yielding consistent neutron star crust and core properties with a provided multivariate Gaussian for bulk nuclear matter parameters.
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Latent-Space Gaussian Processes for Dark-Energy Reconstruction from Observational \(H(z)\) Data
Latent-f and latent-H Gaussian process reconstructions from OHD data both yield f(z), w(z), and Om(z) consistent with Lambda-CDM, with no strong predictive preference and small prior-dependent residuals mainly at high redshift.