110 citations · 253 across the 12 of their papers we have counts for
5 papers · 1 filter
Flexible Gravitational-Wave Parameter Estimation with Transformers
Annalena Kofler, Maximilian Dax, Stephen R. Green +6
Gravitational-wave data analysis relies on accurate and efficient methods to extract physical information from noisy detector signals, yet the increasing rate and complexity of obs…
Real-time gravitational-wave inference for binary neutron stars using machine learning
Maximilian Dax, Stephen R. Green, Jonathan Gair +7
Mergers of binary neutron stars (BNSs) emit signals in both the gravitational-wave (GW) and electromagnetic (EM) spectra. Famously, the 2017 multi-messenger observation of GW170817…
Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA
Nihar Gupte, Antoni Ramos-Buades, Alessandra Buonanno +9
Binary black holes (BBHs) in eccentric orbits produce distinct modulations in gravitational waves (GWs); measuring orbital eccentricity provides evidence for dynamical binary forma…
Adapting to noise distribution shifts in flow-based gravitational-wave inference
Jonas Wildberger, Maximilian Dax, Stephen R. Green +5
Deep learning techniques for gravitational-wave parameter estimation have emerged as a fast alternative to standard samplers $\unicode{x2013}$ producing results of comparable accur…
Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference
Maximilian Dax, Stephen R. Green, Jonathan Gair +5
We combine amortized neural posterior estimation with importance sampling for fast and accurate gravitational-wave inference. We first generate a rapid proposal for the Bayesian po…