Papers#

Applications#

“Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation“ Cole+ https://arxiv.org/abs/2111.08030

“Estimating the warm dark matter mass from strong lensing images with truncated marginal neural ratio estimation” Anau Montel+, https://arxiv.org/abs/2205.09126
“SICRET: Supernova Ia Cosmology with truncated marginal neural Ratio EsTimation” Karchev+ https://arxiv.org/abs/2209.06733
“One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses” Coogan+ https://arxiv.org/abs/2209.09918
“Detection is truncation: studying source populations with truncated marginal neural ratio estimation” Anau Montel+ https://arxiv.org/abs/2211.04291

“Debiasing Standard Siren Inference of the Hubble Constant with Marginal Neural Ratio Estimation” Gagnon-Hartman+ https://arxiv.org/abs/2301.05241
“Constraining the X-ray heating and reionization using 21-cm power spectra with Marginal Neural Ratio Estimation” Saxena+ https://arxiv.org/abs/2303.07339
“Peregrine: Sequential simulation-based inference for gravitational wave signals”, Bhardwaj+ https://arxiv.org/abs/2304.02035
“Albatross: A scalable simulation-based inference pipeline for analysing stellar streams in the Milky Way”, Alvey+ https://arxiv.org/abs/2304.02032