3 papers
gr-qc2026
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…
hep-ex2025
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…
astro-ph.IM2025
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…