Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound

30 April 2022

Martin Vechev

Papers citing "Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound"

50 / 63 papers shown

Title
Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Kota Fukuda Guanqin Zhang Zhenya Zhang Yulei Sui Jianjun Zhao 47 0 0 02 May 2025
Towards Robust LLMs: an Adversarial Robustness Measurement Framework Natan Levy Adiel Ashrov Guy Katz AAML 29 0 0 24 Apr 2025
BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Keyi Shen Jiangwei Yu Huan Zhang Yunzhu Li Yunzhu Li 98 1 0 12 Dec 2024
Testing Neural Network Verifiers: A Soundness Benchmark with Hidden Counterexamples Xingjian Zhou Hongji Xu Andy Xu Zhouxing Shi Cho-Jui Hsieh Huan Zhang AAML 82 0 0 04 Dec 2024
Specification Generation for Neural Networks in Systems Isha Chaudhary Shuyi Lin Cheng Tan Gagandeep Singh 75 0 0 04 Dec 2024
Certified Training with Branch-and-Bound: A Case Study on Lyapunov-stable Neural Control Zhouxing Shi Cho-Jui Hsieh Huan Zhang 77 0 0 27 Nov 2024
Tightening convex relaxations of trained neural networks: a unified approach for convex and S-shaped activations Pablo Carrasco Gonzalo Muñoz 59 2 0 30 Oct 2024
SEEV: Synthesis with Efficient Exact Verification for ReLU Neural Barrier Functions Hongchao Zhang Zhizhen Qin Sicun Gao Andrew Clark 32 1 0 27 Oct 2024
Make Interval Bound Propagation great again Patryk Krukowski Daniel Wilczak Jacek Tabor Anna Bielawska Przemysław Spurek OOD AAML 39 0 0 04 Oct 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
Training Safe Neural Networks with Global SDP Bounds Roman Soletskyi David "davidad" Dalrymple AAML 26 0 0 15 Sep 2024
Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation Ben Batten Yang Zheng Alessandro De Palma Panagiotis Kouvaros A. Lomuscio AAML 38 0 0 23 Aug 2024
PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks Xiyue Zhang Benjie Wang Marta Kwiatkowska Huan Zhang AAML 38 2 0 17 Aug 2024
ModelVerification.jl: a Comprehensive Toolbox for Formally Verifying Deep Neural Networks Tianhao Wei Luca Marzari Kai S. Yun Hanjiang Hu Peizhi Niu Xusheng Luo Changliu Liu 45 0 0 30 Jun 2024
FullCert: Deterministic End-to-End Certification for Training and Inference of Neural Networks Tobias Lorenz Marta Kwiatkowska Mario Fritz AAML 25 0 0 17 Jun 2024
CTBENCH: A Library and Benchmark for Certified Training Yuhao Mao Stefan Balauca Martin Vechev OOD 47 5 0 07 Jun 2024
Towards General Robustness Verification of MaxPool-based Convolutional Neural Networks via Tightening Linear Approximation Yuan Xiao Shiqing Ma Juan Zhai Chunrong Fang Jinyuan Jia Zhenyu Chen AAML 51 1 0 02 Jun 2024
Compact Optimality Verification for Optimization Proxies Wenbo Chen Haoruo Zhao Mathieu Tanneau Pascal Van Hentenryck 38 0 0 31 May 2024
Neural Network Verification with Branch-and-Bound for General Nonlinearities Zhouxing Shi Qirui Jin Zico Kolter Suman Jana Cho-Jui Hsieh Huan Zhang 48 11 0 31 May 2024
Probabilistic Verification of Neural Networks using Branch and Bound David Boetius Stefan Leue Tobias Sutter 42 1 0 27 May 2024
Relational DNN Verification With Cross Executional Bound Refinement Debangshu Banerjee Gagandeep Singh AAML 29 5 0 16 May 2024
Formal Verification of Graph Convolutional Networks with Uncertain Node Features and Uncertain Graph Structure Tobias Ladner Michael Eichelbeck Matthias Althoff GNN 63 0 0 23 Apr 2024
DeepCDCL: An CDCL-based Neural Network Verification Framework Zongxin Liu Pengfei Yang Lijun Zhang Xiaowei Huang 30 3 0 12 Mar 2024
Set-Based Training for Neural Network Verification Lukas Koller Tobias Ladner Matthias Althoff AAML 51 1 0 26 Jan 2024
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks Haoze Wu Omri Isac Aleksandar Zeljić Teruhiro Tagomori M. Daggitt ... Min Wu Min Zhang Ekaterina Komendantskaya Guy Katz Clark W. Barrett 47 31 0 25 Jan 2024
Comparing Differentiable Logics for Learning Systems: A Research Preview Thomas Flinkow Ba Pearlmutter Rosemary Monahan 17 2 0 16 Nov 2023
Exact Verification of ReLU Neural Control Barrier Functions Hongchao Zhang Junlin Wu Yevgeniy Vorobeychik Andrew Clark AAML 43 12 0 13 Oct 2023
Expediting Neural Network Verification via Network Reduction Yuyi Zhong Ruiwei Wang Siau-Cheng Khoo AAML 24 2 0 07 Aug 2023
A DPLL(T) Framework for Verifying Deep Neural Networks Hai V. Duong Thanh-Dat Nguyen Matthew B. Dwyer 25 8 0 17 Jul 2023
Towards a Certified Proof Checker for Deep Neural Network Verification Remi Desmartin Omri Isac Grant Passmore Kathrin Stark Guy Katz Ekaterina Komendantskaya 18 6 0 12 Jul 2023
Verifying Global Neural Network Specifications using Hyperproperties David Boetius Stefan Leue AAML 23 0 0 21 Jun 2023
GPU-Accelerated Verification of Machine Learning Models for Power Systems Samuel C. Chevalier Ilgiz Murzakhanov Spyros Chatzivasileiadis 29 4 0 18 Jun 2023
Understanding Certified Training with Interval Bound Propagation Yuhao Mao Mark Niklas Muller Marc Fischer Martin Vechev AAML 58 15 0 17 Jun 2023
Precise and Generalized Robustness Certification for Neural Networks Yuanyuan Yuan Shuai Wang Z. Su AAML 51 2 0 11 Jun 2023
From Robustness to Explainability and Back Again Xuanxiang Huang Sasha Rubin 34 10 0 05 Jun 2023
Expressive Losses for Verified Robustness via Convex Combinations Alessandro De Palma Rudy Bunel Krishnamurthy Dvijotham M. P. Kumar Robert Stanforth A. Lomuscio AAML 35 12 0 23 May 2023
DeepBern-Nets: Taming the Complexity of Certifying Neural Networks using Bernstein Polynomial Activations and Precise Bound Propagation Haitham Khedr Yasser Shoukry 47 5 0 22 May 2023
Efficient Error Certification for Physics-Informed Neural Networks Francisco Eiras Adel Bibi Rudy Bunel Krishnamurthy Dvijotham Philip Torr M. P. Kumar PINN 26 1 0 17 May 2023
TAPS: Connecting Certified and Adversarial Training Yuhao Mao Mark Niklas Muller Marc Fischer Martin Vechev AAML 31 10 0 08 May 2023
Provable Preimage Under-Approximation for Neural Networks (Full Version) Xiyue Zhang Benjie Wang Marta Z. Kwiatkowska AAML 36 7 0 05 May 2023
Fully Automatic Neural Network Reduction for Formal Verification Tobias Ladner Matthias Althoff AAML 34 3 0 03 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 33 0 29 Apr 2023
Architecture-Preserving Provable Repair of Deep Neural Networks Zhe Tao Stephanie Nawas Jacqueline Mitchell Aditya V. Thakur AAML 34 10 0 07 Apr 2023
Incremental Verification of Neural Networks Shubham Ugare Debangshu Banerjee Sasa Misailovic Gagandeep Singh 38 11 0 04 Apr 2023
CGDTest: A Constrained Gradient Descent Algorithm for Testing Neural Networks Vineel Nagisetty Laura Graves Guanting Pan Piyush Jha Vijay Ganesh AAML OOD 34 1 0 04 Apr 2023
Efficient Certified Training and Robustness Verification of Neural ODEs Mustafa Zeqiri Mark Niklas Muller Marc Fischer Martin Vechev AAML 43 2 0 09 Mar 2023
Provably Bounding Neural Network Preimages Suhas Kotha Christopher Brix Zico Kolter Krishnamurthy Dvijotham Huan Zhang AAML 38 12 0 02 Feb 2023
Interpreting Robustness Proofs of Deep Neural Networks Debangshu Banerjee Avaljot Singh Gagandeep Singh AAML 29 5 0 31 Jan 2023
A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks David Boetius Stefan Leue Tobias Sutter 30 4 0 26 Jan 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 38 66 0 14 Jan 2023