Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization

10 December 2020

Papers citing "Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization"

8 / 8 papers shown

Title
Compositional Curvature Bounds for Deep Neural Networks Taha Entesari Sina Sharifi Mahyar Fazlyab AAML 44 0 0 07 Jun 2024
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization Mahyar Fazlyab Taha Entesari Aniket Roy Ramalingam Chellappa AAML 16 11 0 29 Sep 2023
A Neurosymbolic Approach to the Verification of Temporal Logic Properties of Learning enabled Control Systems Navid Hashemi Bardh Hoxha Tomoya Yamaguchi Danil Prokhorov Geogios Fainekos Jyotirmoy Deshmukh 33 8 0 07 Mar 2023
Convolutional Neural Networks as 2-D systems Dennis Gramlich Patricia Pauli C. Scherer Frank Allgöwer C. Ebenbauer 3DV 36 8 0 06 Mar 2023
ReachLipBnB: A branch-and-bound method for reachability analysis of neural autonomous systems using Lipschitz bounds Taha Entesari Sina Sharifi Mahyar Fazlyab 46 6 0 01 Nov 2022
A Domain-Theoretic Framework for Robustness Analysis of Neural Networks Can Zhou R. A. Shaikh Yiran Li Amin Farjudian OOD 41 4 0 01 Mar 2022
Neural network training under semidefinite constraints Patricia Pauli Niklas Funcke Dennis Gramlich Mohamed Amine Msalmi Frank Allgöwer GAN 18 13 0 03 Jan 2022
Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliers Patricia Pauli Dennis Gramlich J. Berberich Frank Allgöwer 25 26 0 31 Mar 2021