71 citations · 112 across the 9 of their papers we have counts for
3 papers · 1 filter
R2DN: Scalable Parameterization of Contracting and Lipschitz Recurrent Deep Networks
Nicholas H. Barbara, Ruigang Wang, Ian R. Manchester
This paper presents the Robust Recurrent Deep Network (R2DN), a scalable parameterization of stable and robust recurrent neural networks for machine learning and data-driven contro…
On Robust Reinforcement Learning with Lipschitz-Bounded Policy Networks
Nicholas H. Barbara, Ruigang Wang, Ian R. Manchester
This paper presents a study of robust policy networks in deep reinforcement learning. We investigate the benefits of policy parameterizations that naturally satisfy constraints on…
RobustNeuralNetworks.jl: a Package for Machine Learning and Data-Driven Control with Certified Robustness
Nicholas H. Barbara, Max Revay, Ruigang Wang +2
Neural networks are typically sensitive to small input perturbations, leading to unexpected or brittle behaviour. We present RobustNeuralNetworks.jl: a Julia package for neural net…