Neural network training under semidefinite constraints

3 January 2022

Papers citing "Neural network training under semidefinite constraints"

9 / 9 papers shown

Title
LipKernel: Lipschitz-Bounded Convolutional Neural Networks via Dissipative Layers Patricia Pauli Ruigang Wang I. Manchester Frank Allgöwer 35 2 0 29 Oct 2024
Identification For Control Based on Neural Networks: Approximately Linearizable Models Maxime Thieffry Alexandre Hache Mohamed Yagoubi Philippe Chevrel 19 0 0 24 Sep 2024
Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees Neelay Junnarkar Murat Arcak Peter M. Seiler 31 2 0 10 Apr 2024
State space representations of the Roesser type for convolutional layers Patricia Pauli Dennis Gramlich Frank Allgöwer 30 2 0 18 Mar 2024
RAYEN: Imposition of Hard Convex Constraints on Neural Networks J. Tordesillas Jonathan P. How Marco Hutter 37 11 0 17 Jul 2023
Lipschitz-bounded 1D convolutional neural networks using the Cayley transform and the controllability Gramian Patricia Pauli Ruigang Wang I. Manchester Frank Allgöwer 37 8 0 20 Mar 2023
Lipschitz constant estimation for 1D convolutional neural networks Patricia Pauli Dennis Gramlich Frank Allgöwer 31 13 0 28 Nov 2022
Synthesis of Stabilizing Recurrent Equilibrium Network Controllers Neelay Junnarkar He Yin Fangda Gu Murat Arcak Peter M. Seiler 16 13 0 31 Mar 2022
Robustness against Adversarial Attacks in Neural Networks using Incremental Dissipativity B. Aquino Arash Rahnama Peter M. Seiler Lizhen Lin Vijay Gupta AAML 30 8 0 25 Nov 2021