181 citations · 377 across the 22 of their papers we have counts for
5 papers · 1 filter
High-Dimensional Bayesian Model Comparison in Cosmology with GPU-accelerated Nested Sampling and Neural Emulators
Toby Lovick, David Yallup, Davide Piras +2
We demonstrate a GPU-accelerated nested sampling framework for efficient high-dimensional Bayesian inference in cosmology. Using JAX-based neural emulators and likelihoods for cosm…
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…
Transfer learning for multifidelity simulation-based inference in cosmology
Alex A. Saoulis, Davide Piras, Niall Jeffrey +3
Simulation-based inference (SBI) enables cosmological parameter estimation when closed-form likelihoods or models are unavailable. However, SBI relies on machine learning for neura…
Anchors no more: Using peculiar velocities to constrain and the primordial Universe without calibrators
Davide Piras, Francesco Sorrenti, Ruth Durrer +1
We develop a novel approach to constrain the Hubble parameter and the primordial power spectrum amplitude using type Ia supernovae (SNIa) data. By considering…
Constraining the primordial power spectrum using a differentiable likelihood
Subarna Chaki, Andrina Nicola, Alessio Spurio Mancini +2
The simplest inflationary models predict the primordial power spectrum (PPS) of curvature perturbations to be nearly scale-invariant. However, various other models of inflation pre…