Probabilistic kilonova prediction from gravitational wave inferred binary neutron star parameters
This paper introduces \textsc{Genova}, a probabilistic framework utilizing conditional normalizing flows to predict kilonova spectra and light curves directly from gravitational wave-inferred binary neutron star parameters, successfully reproducing observed data from GW170817/AT2017gfo while accounting for both source uncertainty and model variations.