High Probability Derivative Bounds for Random tanh Neural Networks on a Hypercube
arXiv:2608.26526v1 Announce Type: new Abstract: We establish high-probability bounds for mixed input derivatives of wide random neural networks whose activation derivatives satisfy a factorial growth