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Max Revay

Orcid: 0000-0002-8954-8907

According to our database1, Max Revay authored at least 11 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Learning Over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System.
[BibTeX]
[DOI]
Ruigang Wang
,
Nicholas Barbara
,
Max Revay
,
Ian R. Manchester
IEEE Control. Syst. Lett., 2023

RobustNeuralNetworks.jl: a Package for Machine Learning and Data-Driven Control with Certified Robustness.
[BibTeX]
[DOI]
Nicholas H. Barbara
,
Max Revay
,
Ruigang Wang
,
Jing Cheng
,
Ian R. Manchester
CoRR, 2023

2022
Distributed Identification of Contracting and/or Monotone Network Dynamics.
[BibTeX]
[DOI]
Max Revay
,
Jack Umenberger
,
Ian R. Manchester
IEEE Trans. Autom. Control., 2022

Convex Clustering for Autocorrelated Time Series.
[BibTeX]
[DOI]
Max Revay
,
Victor Solo
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
A Convex Parameterization of Robust Recurrent Neural Networks.
[BibTeX]
[DOI]
Max Revay
,
Ruigang Wang
,
Ian R. Manchester
IEEE Control. Syst. Lett., 2021

Recurrent Equilibrium Networks: Unconstrained Learning of Stable and Robust Dynamical Models.
[BibTeX]
[DOI]
Max Revay
,
Ruigang Wang
,
Ian R. Manchester
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Contraction-Based Methods for Stable Identification and Robust Machine Learning: a Tutorial.
[BibTeX]
[DOI]
Ian R. Manchester
,
Max Revay
,
Ruigang Wang
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020
Lipschitz Bounded Equilibrium Networks.
[BibTeX]
[DOI]
Max Revay
,
Ruigang Wang
,
Ian R. Manchester
CoRR, 2020

Convex Sets of Robust Recurrent Neural Networks.
[BibTeX]
[DOI]
Max Revay
,
Ruigang Wang
,
Ian R. Manchester
CoRR, 2020

Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability.
[BibTeX]
[DOI]
Max Revay
,
Ian R. Manchester
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

2019
Distributed Nonlinear Control Design Using Separable Control Contraction Metrics.
[BibTeX]
[DOI]
Humberto Stein Shiromoto
,
Max Revay
,
Ian R. Manchester
IEEE Trans. Control. Netw. Syst., 2019


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