Deep Learning;Hands;Astrophysics;Computational Modeling;Neural Networks;Stars;Predictive Models;Explosions;Nickel;Computational Efficiency;supernovae;astrophysics;astronomy;machine Learning;deep Learning;neural Networks;time-Series
In this work, we present a Deep Learning framework to predict the progenitor star’s characteristics of Supernovae (SNe) from their observed light curves. This task is crucial for astrophysics, as it can provide insights into the evolution of the star …