249 citations · 252 across the 6 of their papers we have counts for
8 papers
Accelerating massive ensembles of ordinary differential equations
Lawrence Berry, Will Handley, Oliver Hahn +1
Solving large ensembles of small, independent ordinary differential equations (ODEs) is a common task in computational science and engineering, arising for example in Bayesian para…
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…
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…
Global structure of the time delay likelihood
Namu Kroupa, Will Handley
We identify a fundamental pathology in the likelihood for time delay inference which challenges standard inference methods. By analysing the likelihood for time delay inference wit…
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…
Resonances in reflective Hamiltonian Monte Carlo
Namu Kroupa, Gábor Csányi, Will Handley
In high dimensions, reflective Hamiltonian Monte Carlo with inexact reflections exhibits slow mixing when the particle ensemble is initialised from a Dirac delta distribution and t…
A foundation model for atomistic materials chemistry
Ilyes Batatia, Philipp Benner, Yuan Chiang +85
Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much…
Kernel-, mean- and noise-marginalised Gaussian processes for exoplanet transits and inference
Namu Kroupa, David Yallup, Will Handley +1
Using a fully Bayesian approach, Gaussian Process regression is extended to include marginalisation over the kernel choice and kernel hyperparameters. In addition, Bayesian model c…