The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification

24 June 2020

Christian Tjandraatmadja

Papers citing "The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification"

23 / 23 papers shown

Title
Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Kota Fukuda Guanqin Zhang Zhenya Zhang Yulei Sui Jianjun Zhao 45 0 0 02 May 2025
Formal Verification of Markov Processes with Learned Parameters Muhammad Maaz Timothy C. Y. Chan 40 0 0 27 Jan 2025
On Using Certified Training towards Empirical Robustness Alessandro De Palma Serge Durand Zakaria Chihani François Terrier Caterina Urban OOD AAML 33 1 0 02 Oct 2024
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 91 32 0 29 Apr 2023
Boosting Verified Training for Robust Image Classifications via Abstraction Zhaodi Zhang Zhiyi Xue Yang Chen Si Liu Yueling Zhang J. Liu Min Zhang 33 4 0 21 Mar 2023
On the tightness of linear relaxation based robustness certification methods Cheng Tang AAML 21 0 0 01 Oct 2022
Provably Tightest Linear Approximation for Robustness Verification of Sigmoid-like Neural Networks Zhaodi Zhang Yiting Wu Siwen Liu Jing Liu Min Zhang AAML 23 11 0 21 Aug 2022
IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound Alessandro De Palma Rudy Bunel Krishnamurthy Dvijotham M. P. Kumar Robert Stanforth AAML 40 17 0 29 Jun 2022
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective Mark Huasong Meng Guangdong Bai Sin Gee Teo Zhe Hou Yan Xiao Yun Lin J. Dong AAML 21 43 0 24 Jun 2022
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound Claudio Ferrari Mark Niklas Muller Nikola Jovanović Martin Vechev 28 82 0 30 Apr 2022
Efficient Neural Network Analysis with Sum-of-Infeasibilities Haoze Wu Aleksandar Zeljić Guy Katz Clark W. Barrett AAML 39 30 0 19 Mar 2022
OMLT: Optimization & Machine Learning Toolkit Francesco Ceccon Jordan Jalving Joshua Haddad Alexander Thebelt Calvin Tsay C. Laird Ruth Misener 32 69 0 04 Feb 2022
Neural Network Verification in Control M. Everett AAML 32 16 0 30 Sep 2021
GoTube: Scalable Stochastic Verification of Continuous-Depth Models Sophie Gruenbacher Mathias Lechner Ramin Hasani Daniela Rus T. Henzinger S. Smolka Radu Grosu 18 17 0 18 Jul 2021
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting Shaoru Chen Eric Wong Zico Kolter Mahyar Fazlyab 39 15 0 16 Jun 2021
PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations Mark Niklas Muller Gleb Makarchuk Gagandeep Singh Markus Püschel Martin Vechev 33 90 0 05 Mar 2021
On the Paradox of Certified Training Nikola Jovanović Mislav Balunović Maximilian Baader Martin Vechev OOD 23 13 0 12 Feb 2021
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification Brendon G. Anderson Ziye Ma Jingqi Li Somayeh Sojoudi 55 1 0 22 Jan 2021
Supermodularity and valid inequalities for quadratic optimization with indicators Alper Atamtürk A. Gómez 18 21 0 29 Dec 2020
Scaling Polyhedral Neural Network Verification on GPUs Christoph Müller F. Serre Gagandeep Singh Markus Püschel Martin Vechev AAML 21 56 0 20 Jul 2020
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 78 292 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 226 1,835 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang M. Kwiatkowska Sen Wang Min Wu AAML 178 932 0 21 Oct 2016