Explainable autoencoder for neutron star dense matter parameter estimation

Francesco Di Clemente, Matteo Scialpi, Michał Bejger

We present a physics-informed autoencoder designed to encode the equation of state of neutron stars into an interpretable latent space. In particular the input will be encoded in t…