The Geometry of the Set of Equivalent Linear Neural Networks
The research investigates the geometric structure of weight vectors that produce a specific linear transformation W in a neural network. It partitions this complex set into smooth manifolds called strata based on how information flows through different layers. This stratification allows researchers to understand the topology and geometry of these weight configurations.