2 citations · 4 across the 10 of their papers we have counts for
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Nested Sampling for ARIMA Model Selection in Astronomical Time-Series Analysis
Ajinkya Naik, Will Handley
The era of large-scale, high-cadence astronomical surveys demands efficient and robust methods for time-series analysis. ARIMA models provide a versatile parametric description of…
: A Public Nested Sampling Database for Bayesian Cosmology
Dily Duan Yi Ong, Will Handley
Bayesian inference is central to modern cosmology. While parameter estimation is achievable with unnormalised posteriors traditionally obtained via MCMC methods, comprehensive mode…
A Bayesian Perspective on Evidence for Evolving Dark Energy
Dily Duan Yi Ong, David Yallup, Will Handley
The DESI Collaboration reports a significant preference for a dynamic dark energy model (CDM) over the cosmological constant (CDM) when their data are combined with othe…
unimpeded: A Public Grid of Nested Sampling Chains for Cosmological Model Comparison and Tension Analysis
Dily Duan Yi Ong, Will Handley
Bayesian inference is central to modern cosmology, yet comprehensive model comparison and tension quantification remain computationally prohibitive for many researchers. To address…
CMB Constraints on Quantized Spatial Curvature in globally CPT-symmetric universes
Wei-Ning Deng, Will Handley
The periodic solution of the Friedmann equation in conformal time, implies that only cosmological perturbations exhibiting corresponding symmetries are physically permissible, lead…
Alleviating the Hubble tension with Torsion Condensation (TorC)
Sinah Legner, Will Handley, Will Barker +1
Constraints on the cosmological parameters of Torsion Condensation (TorC) are investigated using Planck 2018 Cosmic Microwave Background data. TorC is a case of Poincaré gauge theo…
Cosmological Parameter Estimation with Sequential Linear Simulation-based Inference
Nicolas Mediato-Diaz, Will Handley
We develop the framework of Linear Simulation-based Inference (LSBI), an application of simulation-based inference where the likelihood is approximated by a Gaussian linear functio…