3.6k citations · 8.4k across the 24 of their papers we have counts for
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Improving the scalability of Gaussian-process error marginalization in gravitational-wave inference
Miaoxin Liu, Xiao-Dong Li, Alvin J. K. Chua
The accuracy of Bayesian inference can be negatively affected by the use of inaccurate forward models. In the case of gravitational-wave inference, accurate but computationally exp…
The Effect of Mission Duration on LISA Science Objectives
Pau Amaro Seoane, Manuel Arca Sedda, Stanislav Babak +38
The science objectives of the LISA mission have been defined under the implicit assumption of a 4 yr continuous data stream. Based on the performance of LISA Pathfinder, it is now…
2 Fast 2 Fiducial: Gaussian processes for the interpolation and marginalization of waveform error in extreme-mass-ratio-inspiral parameter estimation
Alvin J. K. Chua, Natalia Korsakova, Christopher J. Moore +2
A number of open problems hinder our present ability to extract scientific information from data that will be gathered by the near-future gravitational-wave mission LISA. Many of t…
Reduced-order modeling with artificial neurons for gravitational-wave inference
Alvin J. K. Chua, Chad R. Galley, Michele Vallisneri
Gravitational-wave data analysis is rapidly absorbing techniques from deep learning, with a focus on convolutional networks and related methods that treat noisy time series as imag…