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Extreme-mass-ratio inspirals (EMRIs) will be an important type ofastrophysical source for future space-based gravitational-wave detectors. Thereis a trade-off between accuracy and computational speed for the EMRI waveformtemplates required in the analysis of data from these detectors. We discuss howthe systematic error incurred by using faster templates may be reduced withimproved models such as augmented kludge waveforms, and marginalised over withstatistical techniques such as Gaussian process regression.

Augmented kludge waveforms and Gaussian process regression for EMRI data analysis