The polynomial composition conjecture implies a complete understanding of the identifiability of deep fully connected neural network architectures with generic polynomial activation functions

the conjecture implies a complete understanding of the identifiability (i.e., parameter symmetries) of deep fully connected neural network architectures with generic polynomial activation functions

http://arxiv.org/abs/2608.27113v1