Mohammed Nabil EL-KORSO

Fisher-Rao Sensitivity for Out-of-Distribution Detection in Deep Neural Networks

Deep neural networks often remain overconfident on Out-of-Distribution (OoD) inputs. We revisit this problem through Riemannian information geometry. We model the network's predictions as a statistical manifold and find that OoD inputs exhibit higher local Fisher-Rao sensitivity. By quantifying this…