The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results

20 December 2022

Changliu Liu

Papers citing "The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results"

32 / 32 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
A Generalised Framework for Property-Driven Machine Learning Thomas Flinkow Marco Casadio Colin Kessler Rosemary Monahan Ekaterina Komendantskaya AAML 62 1 0 01 May 2025
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
Creating a Formally Verified Neural Network for Autonomous Navigation: An Experience Report Syed Ali Asadullah Bukhari Thomas Flinkow M. Inkarbekov Barak A. Pearlmutter Rosemary Monahan 72 0 0 21 Nov 2024
Verification of Neural Networks against Convolutional Perturbations via Parameterised Kernels Benedikt Brückner Alessio Lomuscio AAML 54 0 0 07 Nov 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 42 0 0 30 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
Probabilistic Verification of Neural Networks using Branch and Bound David Boetius Stefan Leue Tobias Sutter 42 0 0 27 May 2024
Monitizer: Automating Design and Evaluation of Neural Network Monitors Muqsit Azeem Marta Grobelna Sudeep Kanav Jan Křetínský Stefanie Mohr Sabine Rieder 39 2 0 16 May 2024
Scalable Exact Verification of Optimization Proxies for Large-Scale Optimal Power Flow Rahul Nellikkath Mathieu Tanneau Pascal Van Hentenryck Spyros Chatzivasileiadis 45 0 0 09 May 2024
Harnessing Neuron Stability to Improve DNN Verification Hai V. Duong Dong Xu ThanhVu Nguyen Matthew B. Dwyer 24 4 0 19 Jan 2024
DEM: A Method for Certifying Deep Neural Network Classifier Outputs in Aerospace Guy Katz Natan Levy Idan Refaeli Raz Yerushalmi AAML 13 0 0 04 Jan 2024
The Pros and Cons of Adversarial Robustness Yacine Izza Sasha Rubin AAML 25 1 0 18 Dec 2023
Comparing Differentiable Logics for Learning Systems: A Research Preview Thomas Flinkow Ba Pearlmutter Rosemary Monahan 12 2 0 16 Nov 2023
Expediting Neural Network Verification via Network Reduction Yuyi Zhong Ruiwei Wang Siau-Cheng Khoo AAML 24 2 0 07 Aug 2023
Robustness Verification of Deep Neural Networks using Star-Based Reachability Analysis with Variable-Length Time Series Input Neelanjana Pal Diego Manzanas Lopez Taylor T. Johnson AI4TS 9 1 0 26 Jul 2023
Adaptive Certified Training: Towards Better Accuracy-Robustness Tradeoffs Zhakshylyk Nurlanov Frank R. Schmidt Florian Bernard OOD 29 0 0 24 Jul 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
Verifying Global Neural Network Specifications using Hyperproperties David Boetius Stefan Leue AAML 18 0 0 21 Jun 2023
Understanding Certified Training with Interval Bound Propagation Yuhao Mao Mark Niklas Muller Marc Fischer Martin Vechev AAML 45 15 0 17 Jun 2023
A Tale of Two Approximations: Tightening Over-Approximation for DNN Robustness Verification via Under-Approximation Zhiyi Xue Si Liu Zhaodi Zhang Yiting Wu M. Zhang AAML 23 2 0 26 May 2023
DeepBern-Nets: Taming the Complexity of Certifying Neural Networks using Bernstein Polynomial Activations and Precise Bound Propagation Haitham Khedr Yasser Shoukry 47 4 0 22 May 2023
TAPS: Connecting Certified and Adversarial Training Yuhao Mao Mark Niklas Muller Marc Fischer Martin Vechev AAML 28 10 0 08 May 2023
CGDTest: A Constrained Gradient Descent Algorithm for Testing Neural Networks Vineel Nagisetty Laura Graves Guanting Pan Piyush Jha Vijay Ganesh AAML OOD 31 1 0 04 Apr 2023
Asymmetric Certified Robustness via Feature-Convex Neural Networks Samuel Pfrommer Brendon G. Anderson Julien Piet Somayeh Sojoudi AAML 14 7 0 03 Feb 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
Open- and Closed-Loop Neural Network Verification using Polynomial Zonotopes Niklas Kochdumper Christian Schilling Matthias Althoff Stanley Bak 28 33 0 06 Jul 2022
Abstraction and Refinement: Towards Scalable and Exact Verification of Neural Networks Jiaxiang Liu Yunhan Xing Xiaomu Shi Fu Song Zhiwu Xu Zhong Ming 21 10 0 02 Jul 2022
Learning Density Distribution of Reachable States for Autonomous Systems Yue Meng Dawei Sun Zeng Qiu Md Tawhid Bin Waez Chuchu Fan 77 19 0 14 Sep 2021
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 30 128 0 09 Sep 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 234 1,837 0 03 Feb 2017