2.4k citations · 13.3k across the 165 of their papers we have counts for
171 papers
Proximal nested sampling with data-driven priors for physical scientists
Jason D. McEwen, Tobías I. Liaudat, Matthew A. Price +2
Proximal nested sampling was introduced recently to open up Bayesian model selection for high-dimensional problems such as computational imaging. The framework is suitable for mode…
Fast emulation of anisotropies induced in the cosmic microwave background by cosmic strings
Matthew A. Price, Matthijs Mars, Matthew M. Docherty +3
Cosmic strings are linear topological defects that may have been produced during symmetry-breaking phase transitions in the very early Universe. In an expanding Universe the existe…
Learned harmonic mean estimation of the marginal likelihood with normalizing flows
Alicja Polanska, Matthew A. Price, Alessio Spurio Mancini +1
Computing the marginal likelihood (also called the Bayesian model evidence) is an important task in Bayesian model selection, providing a principled quantitative way to compare mod…
The Tiny Time-series Transformer: Low-latency High-throughput Classification of Astronomical Transients using Deep Model Compression
Tarek Allam, Julien Peloton, Jason D. McEwen
A new golden age in astronomy is upon us, dominated by data. Large astronomical surveys are broadcasting unprecedented rates of information, demanding machine learning as a critica…
Slepian Scale-Discretised Wavelets on Manifolds
Patrick J. Roddy, Jason D. McEwen
Inspired by recent interest in geometric deep learning, this work generalises the recently developed Slepian scale-discretised wavelets on the sphere to Riemannian manifolds. Throu…
Learned Interferometric Imaging for the SPIDER Instrument
Matthijs Mars, Marta M. Betcke, Jason D. McEwen
The Segmented Planar Imaging Detector for Electro-Optical Reconnaissance (SPIDER) is an optical interferometric imaging device that aims to offer an alternative to the large space…