Example Neural Networks
get_example_network_params imports the weights of networks verified in our paper, as well as other networks of interest, as NeuralNets that can immediately be verified via our tools.
Index
Public Interface
MIPVerify.get_example_network_params — Method.get_example_network_params(name)
Makes named example neural networks available as a NeuralNet object.
Arguments
name::String: Name of example neural network. Options:'MNIST.n1':Architecture: Two fully connected layers with 40 and 20 units.
Training: Trained regularly with no attempt to increase robustness.
'MNIST.WK17a_linf0.1_authors'.Architecture: Two convolutional layers (stride length 2) with 16 and 32 filters respectively (size 4 × 4 in both layers), followed by a fully-connected layer with 100 units.
Training: Network trained to be robust to attacks with $l_\infty$ norm at most 0.1 via method in Provable defenses against adversarial examples via the convex outer adversarial polytope. Is MNIST network for which results are reported in that paper.
'MNIST.RSL18a_linf0.1_authors'.Architecture: One fully connected layer with 500 units.
Training: Network trained to be robust to attacks with $l_\infty$ norm at most 0.1 via method in Certified Defenses against Adversarial Examples . Is MNIST network for which results are reported in that paper.