Max Revay
Title
Cited by
Cited by
Year
3D printable geomaterials
DAH Hanaor, Y Gan, M Revay, DW Airey, I Einav
Géotechnique 66 (4), 323-332, 2016
412016
Contracting implicit recurrent neural networks: Stable models with improved trainability
M Revay, I Manchester
Learning for Dynamics and Control, 393-403, 2020
92020
Distributed nonlinear control design using separable control contraction metrics
HS Shiromoto, M Revay, IR Manchester
IEEE Transactions on Control of Network Systems 6 (4), 1281-1290, 2018
62018
A convex parameterization of robust recurrent neural networks
M Revay, R Wang, IR Manchester
IEEE Control Systems Letters 5 (4), 1363-1368, 2020
52020
Lipschitz Bounded Equilibrium Networks
M Revay, R Wang, IR Manchester
arXiv preprint arXiv:2010.01732, 2020
22020
Convex sets of robust recurrent neural networks
M Revay, R Wang, IR Manchester
arXiv e-prints, arXiv: 2004.05290, 2020
12020
Recurrent Equilibrium Networks: Flexible Dynamic Models with Guaranteed Stability and Robustness
M Revay, R Wang, IR Manchester
arXiv preprint arXiv:2104.05942, 2021
2021
Recurrent Equilibrium Networks: Unconstrained Learning of Stable and Robust Dynamical Models
M Revay, R Wang, IR Manchester
arXiv preprint arXiv:2104.05942, 2021
2021
Distributed Nonlinear Control Design using Separable Control Contraction Metrics
H Stein Shiromoto, M Revay, IR Manchester
arXiv e-prints, arXiv: 1810.04794, 2018
2018
3D printable geomaterials
D Airey, I Einav, Y Gan, D Hanaor, M Revay
ICE Publishing, 2016
2016
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