158 citations · 208 across the 18 of their papers we have counts for
9 papers · 1 filter
Neural Transport Nested Sampling
David Yallup, Will Handley
Sampling from Boltzmann distributions of molecular systems is an inference problem that has seen significant recent developments fuelled by advances in neural density estimation. W…
Quenched Ensemble Sampling
David Yallup
Some of the sharpest challenges in sampling from the energy functions of physical systems arise at phase transitions, where the density of states changes abruptly and many sampling…
Ab Initio Real-Time Gravitational-Wave Parameter Estimation
David Yallup, Metha Prathaban, James Alvey +4
We present a specialised GPU-native nested sampling kernel targeting rapid parameter estimation for gravitational wave inference problems. Building upon a Slice-within-Gibbs (SwiG)…
Rapid Hubble constant inference from GW170817 using GPU-accelerated nested sampling: prior sensitivity and the limits of post-hoc reweighting
Ming Han Yang, Metha Prathaban, David Yallup +1
The bright-siren measurement of the Hubble constant from GW170817 (Abbott et al. 2017) assumes that switching from a volumetric to a uniform-in- luminosity-distance prior can…
Automatic Laplace Collapsed Sampling: Scalable Marginalisation of Latent Parameters via Automatic Differentiation
Toby Lovick, David Yallup, Will Handley
We present Automatic Laplace Collapsed Sampling (ALCS), a general framework for marginalising latent parameters in Bayesian models using automatic differentiation, which we combine…
The Bayesian view of DESI DR2 with unimpeded: Evidence and tension in a combined analysis with CMB and supernovae across cosmological models
Dily Duan Yi Ong, David Yallup, Will Handley
We apply the framework to perform a fully Bayesian reanalysis of the DESI DR2 data, using nested sampling with to compute evidences for $Λ…
Time delays and stationarity in quasar light curves
Namu Kroupa, David Yallup, Will Handley
We present a fully Bayesian framework for time delay inference and stationarity tests in quasar light curves using marginalised Gaussian processes. The model separates a determinis…
Nested Sampling with Slice-within-Gibbs: Efficient Evidence Calculation for Hierarchical Bayesian Models
David Yallup
We present Nested Sampling with Slice-within-Gibbs (NS-SwiG), an algorithm for Bayesian inference and evidence estimation in high-dimensional models whose likelihood admits a facto…
Nested Slice Sampling: Vectorized Nested Sampling for GPU-Accelerated Inference
David Yallup, Namu Kroupa, Will Handley
Model comparison and calibrated uncertainty quantification often require integrating over parameters, but scalable inference can be challenging for complex, multimodal targets. Nes…