7 citations · 15 across the 4 of their papers we have counts for
4 papers
Leveraging rapid parameter estimates for efficient gravitational-wave Bayesian inference via posterior repartitioning
Metha Prathaban, Charlie Hoy, Michael J. Williams
Gravitational-wave astronomy typically relies on rigorous, computationally expensive Bayesian analyses. Several methods have also been developed to perform rapid, approximate Bayes…
Accelerated Sequential Posterior Inference via Reuse for Gravitational-Wave Analyses
Michael J. Williams
We introduce Accelerated Sequential Posterior Inference via Reuse (ASPIRE), a broadly applicable framework that transforms existing posterior samples and Bayesian evidence estimate…
Validating Sequential Monte Carlo for Gravitational-Wave Inference
Michael J. Williams, Minas Karamanis, Yilin Luo +1
Nested sampling (NS) is the preferred stochastic sampling algorithm for gravitational-wave inference for compact binary coalenscences (CBCs). It can handle the complex nature of th…
First investigation of void statistics in numerical relativity simulations
Michael J. Williams, Hayley J. Macpherson, David L. Wiltshire +1
We apply and extend standard tools for void statistics to cosmological simulations that solve Einstein's equations with numerical relativity (NR). We obtain a simulated void catalo…