A singular Riemannian geometry approach to Deep Neural Networks II. Reconstruction of 1-D equivalence classes

Abstract

The equivalence classes are sets of points that are mapped in the same way by the Neural Network• We reconstruct equivalence classes of a given label in the NN input manifold• We develop a strategy to step from an equivalence class to another in input manifold• We apply the developed algorithms to thermodynamics and classification problems