Neural Network Verification with Branch-and-Bound for General
Nonlinearities
Neural Network Verification with Branch-and-Bound for General
Nonlinearities
Branch-and-bound (BaB) is among the most effective methods for neural network (NN) verification. However, existing works on BaB have mostly focused on NNs with piecewise linear activations, especially ReLU networks. In this paper, we develop a general framework, named GenBaB, to conduct BaB for general nonlinearities in general computational graphs …