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A Physics Informed Bayesian Neural Network for the Neutron Star Equation of State
We present a physics-informed Bayesian neural-network framework for inferring neutron-star equations of state from theoretical priors and propagating the resulting uncertainty to stellar observables. Trained on a representative set of hadronic EoSs, the model learns the equation of state through sto
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