Lagrangian Decomposition for Neural Network Verification

Lagrangian Decomposition for Neural Network Verification

24 February 2020

Alessandro De Palma

Alban Desmaison

Krishnamurthy Dvijotham

Philip H. S. Torr

Papers citing "Lagrangian Decomposition for Neural Network Verification"

19 / 19 papers shown

Title
BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Keyi Shen Jiangwei Yu Huan Zhang Yunzhu Li Yunzhu Li 87 1 0 12 Dec 2024
On Using Certified Training towards Empirical Robustness Alessandro De Palma Serge Durand Zakaria Chihani François Terrier Caterina Urban OOD AAML 38 1 0 02 Oct 2024
Probabilistic Verification of Neural Networks using Branch and Bound David Boetius Stefan Leue Tobias Sutter 42 0 0 27 May 2024
Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques Sophie A. Neubauer Radu Grosu 20 0 0 23 Aug 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
First Three Years of the International Verification of Neural Networks Competition (VNN-COMP) Christopher Brix Mark Niklas Muller Stanley Bak Taylor T. Johnson Changliu Liu NAI 30 66 0 14 Jan 2023
ReachLipBnB: A branch-and-bound method for reachability analysis of neural autonomous systems using Lipschitz bounds Taha Entesari Sina Sharifi Mahyar Fazlyab 39 6 0 01 Nov 2022
Sound and Complete Verification of Polynomial Networks Elias Abad Rocamora Mehmet Fatih Şahin Fanghui Liu Grigorios G. Chrysos V. Cevher 23 5 0 15 Sep 2022
IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound Alessandro De Palma Rudy Bunel Krishnamurthy Dvijotham M. P. Kumar Robert Stanforth AAML 42 17 0 29 Jun 2022
Efficient Neural Network Analysis with Sum-of-Infeasibilities Haoze Wu Aleksandar Zeljić Guy Katz Clark W. Barrett AAML 47 30 0 19 Mar 2022
The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results Stanley Bak Changliu Liu Taylor T. Johnson NAI 19 112 0 31 Aug 2021
Neural Network Branch-and-Bound for Neural Network Verification Florian Jaeckle Jingyue Lu M. P. Kumar 18 8 0 27 Jul 2021
GoTube: Scalable Stochastic Verification of Continuous-Depth Models Sophie Gruenbacher Mathias Lechner Ramin Hasani Daniela Rus T. Henzinger S. Smolka Radu Grosu 23 17 0 18 Jul 2021
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting Shaoru Chen Eric Wong Zico Kolter Mahyar Fazlyab 47 15 0 16 Jun 2021
An efficient nonconvex reformulation of stagewise convex optimization problems Rudy Bunel Oliver Hinder Srinadh Bhojanapalli Krishnamurthy Dvijotham Dvijotham OffRL 27 14 0 27 Oct 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 27 128 0 09 Sep 2020
Algorithms for Verifying Deep Neural Networks Changliu Liu Tomer Arnon Christopher Lazarus Christopher A. Strong Clark W. Barrett Mykel J. Kochenderfer AAML 30 390 0 15 Mar 2019
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 88 292 0 09 Aug 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 231 1,837 0 03 Feb 2017