Dr. Michael Pürrer
Dr. Michael Pürrer
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Surrogate model
Deep learning surrogate model of gravitational waves
Deep learning algorithms have the potential to dramatically improve predictive models of chirp like gravitational waves.
Frequency-domain reduced-order model of aligned-spin effective-one-body waveforms with higher-order modes
Enhancing Gravitational-Wave Science with Machine Learning
Regression methods in waveform modeling: a comparative study
Surrogate model for an aligned-spin effective-one-body waveform model of binary neutron star inspirals using Gaussian process regression
Surrogate models of gravitational waves
Accelerating semi-analytic models of gravitational waves.
Accelerating parameter estimation of gravitational waves from black hole binaries with reduced order quadratures
Can we measure individual black-hole spins from gravitational-wave observations?
Improved effective-one-body model of spinning, nonprecessing binary black holes for the era of gravitational-wave astrophysics with advanced detectors
Fast and accurate inference on gravitational waves from precessing compact binaries
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