Related talks and presentations

05 Dec 2019

Gaussian process regression for gravitational astrophysics

Workshop on Machine Learning in Astronomy and Astrophysics
Seoul, South Korea

Project name: heron

Dates: 2015-10-01 - Present

Project Status: Ongoing

Project Description
Understanding the waveform for a binary black hole coalescence is important for a number of data analysis tasks in gravitational wave astronomy, including parameter estimation and testing General Relativity. Producing precise waveforms is slow and computationally intensive, however. This project involves the development of accurate surrogate models which can be used in Bayesian inference.