Max Revay

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 19

Top Topics

Recurrent Neural Networks

Top Venues

IEEE Control. Syst. Lett.

IEEE Trans. Autom. Control.

Publications

Max Revay, Ruigang Wang, Ian R. Manchester
Recurrent Equilibrium Networks: Flexible Dynamic Models With Guaranteed Stability and Robustness. IEEE Trans. Autom. Control. 69 (5) (2024)
Nicholas H. Barbara, Max Revay, Ruigang Wang, Jing Cheng, Ian R. Manchester
RobustNeuralNetworks.jl: a Package for Machine Learning and Data-Driven Control with Certified Robustness. CoRR (2023)
Ruigang Wang, Nicholas Barbara, Max Revay, Ian R. Manchester
Learning Over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System. IEEE Control. Syst. Lett. 7 (2023)
Max Revay, Victor Solo
Convex Clustering for Autocorrelated Time Series. ICASSP (2022)
Max Revay, Jack Umenberger, Ian R. Manchester
Distributed Identification of Contracting and/or Monotone Network Dynamics. IEEE Trans. Autom. Control. 67 (7) (2022)
Max Revay, Ruigang Wang, Ian R. Manchester
Recurrent Equilibrium Networks: Unconstrained Learning of Stable and Robust Dynamical Models. CDC (2021)
Ruigang Wang, Nicholas Barbara, Max Revay, Ian R. Manchester
Learning over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System. CoRR (2021)
Ian R. Manchester, Max Revay, Ruigang Wang
Contraction-Based Methods for Stable Identification and Robust Machine Learning: a Tutorial. CDC (2021)
Max Revay, Jack Umenberger, Ian R. Manchester
Distributed Identification of Contracting and/or Monotone Network Dynamics. CoRR (2021)
Max Revay, Ruigang Wang, Ian R. Manchester
A Convex Parameterization of Robust Recurrent Neural Networks. IEEE Control. Syst. Lett. 5 (4) (2021)
Max Revay, Ruigang Wang, Ian R. Manchester
A Convex Parameterization of Robust Recurrent Neural Networks. ACC (2021)
Max Revay, Ruigang Wang, Ian R. Manchester
Recurrent Equilibrium Networks: Unconstrained Learning of Stable and Robust Dynamical Models. CoRR (2021)
Ian R. Manchester, Max Revay, Ruigang Wang
Contraction-Based Methods for Stable Identification and Robust Machine Learning: a Tutorial. CoRR (2021)
Max Revay, Ruigang Wang, Ian R. Manchester
Convex Sets of Robust Recurrent Neural Networks. CoRR (2020)
Max Revay, Ian R. Manchester
Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability. L4DC (2020)
Max Revay, Ruigang Wang, Ian R. Manchester
Lipschitz Bounded Equilibrium Networks. CoRR (2020)
Max Revay, Ian R. Manchester
Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability. CoRR (2019)
Humberto Stein Shiromoto, Max Revay, Ian R. Manchester
Distributed Nonlinear Control Design Using Separable Control Contraction Metrics. IEEE Trans. Control. Netw. Syst. 6 (4) (2019)
Humberto Stein Shiromoto, Max Revay, Ian R. Manchester
Distributed Nonlinear Control Design using Separable Control Contraction Metrics. CoRR (2018)