Derives layer-wise recursions for finite-width tensors under orthogonal initialization that reproduce the observed large-depth stability of nonlinear networks.
The expectation value is taken over the decorations of the internal lines attached to the propagator, which obeys the same selection rules described in [13]
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Criticality and Saturation in Orthogonal Neural Networks
Derives layer-wise recursions for finite-width tensors under orthogonal initialization that reproduce the observed large-depth stability of nonlinear networks.