RobustNeuralNetworks.jl
A Julia package for robust neural networks built from the Recurrent Equilibrium Network (REN) and Lipschitz-Bounded Deep Network (LBDN) model classes. Please visit the docs page for detailed documentation
Installation
To install the package, type the following into the REPL.
] add RobustNeuralNetworks
You should now be able to construct robust neural network models. The following example constructs a contracting REN and evalutates it given a batch of random initial states x0 and inputs u0.
using Random
using RobustNeuralNetworks
# Setup
rng = MersenneTwister(42)
batches = 10
nu, nx, nv, ny = 4, 2, 20, 1
# Construct a REN
contracting_ren_ps = ContractingRENParams{Float64}(nu, nx, nv, ny; rng=rng)
ren = REN(contracting_ren_ps)
# Some random inputs
x0 = init_states(ren, batches; rng=rng)
u0 = randn(rng, ren.nu, batches)
# Evaluate the REN over one timestep
x1, y1 = ren(x0, u0)
println(round.(y1;digits=2))The output should be:
[-31.41 0.57 -0.55 -3.56 -35.0 -18.28 -25.48 -7.49 -4.14 15.31]Contact
Please contact Nic Barbara (nicholas.barbara@sydney.edu.au) with any questions.