Reachability Analysis of Deep Neural Networks with Provable Guarantees

6 May 2018

Papers citing "Reachability Analysis of Deep Neural Networks with Provable Guarantees"

50 / 68 papers shown

Title
Control Invariant Sets for Neural Network Dynamical Systems and Recursive Feasibility in Model Predictive Control Xiao Li Tianhao Wei Changliu Liu Anouck Girard Ilya Kolmanovsky 17 0 0 15 May 2025
Feature Relevancy, Necessity and Usefulness: Complexity and Algorithms Tomás Capdevielle Santiago Cifuentes FAtt 45 0 0 06 May 2025
Probabilistic Verification of Neural Networks using Branch and Bound David Boetius Stefan Leue Tobias Sutter 45 1 0 27 May 2024
Extending Neural Network Verification to a Larger Family of Piece-wise Linear Activation Functions László Antal Hana Masara Erika Ábrahám 41 0 0 16 Nov 2023
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems Saddek Bensalem Chih-Hong Cheng Wei Huang Xiaowei Huang Changshun Wu Xingyu Zhao AAML 32 6 0 20 Jul 2023
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation Xiaowei Huang Wenjie Ruan Wei Huang Gao Jin Yizhen Dong ... Sihao Wu Peipei Xu Dengyu Wu André Freitas Mustafa A. Mustafa ALM 52 83 0 19 May 2023
Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz D. Bhutto Bo Zhu J. Liu Neha Koonjoo H. Li Bruce Rosen Matthew S. Rosen UQCV OOD 15 2 0 12 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
POLAR-Express: Efficient and Precise Formal Reachability Analysis of Neural-Network Controlled Systems Yixuan Wang Weichao Zhou Jiameng Fan Zhilu Wang Jiajun Li Xin Chen Chao Huang Wenchao Li Qi Zhu 41 15 0 31 Mar 2023
Reachability Analysis of Neural Network Control Systems Chi Zhang W. Ruan Peipei Xu 31 14 0 28 Jan 2023
Certified Policy Smoothing for Cooperative Multi-Agent Reinforcement Learning Ronghui Mu Wenjie Ruan Leandro Soriano Marcolino Gaojie Jin Q. Ni 42 5 0 22 Dec 2022
Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking Dennis Gross T. D. Simão N. Jansen G. Pérez AAML 51 2 0 10 Dec 2022
Provably Tightest Linear Approximation for Robustness Verification of Sigmoid-like Neural Networks Zhaodi Zhang Yiting Wu Siwen Liu Jing Liu Min Zhang AAML 29 11 0 21 Aug 2022
Lipschitz Bound Analysis of Neural Networks S. Bose AAML 42 0 0 14 Jul 2022
Reachability Analysis of a General Class of Neural Ordinary Differential Equations Diego Manzanas Lopez Patrick Musau Nathaniel P. Hamilton Taylor T. Johnson 23 14 0 13 Jul 2022
PRoA: A Probabilistic Robustness Assessment against Functional Perturbations Tianle Zhang Wenjie Ruan J. Fieldsend AAML 18 21 0 05 Jul 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 Jin Song Dong AAML 32 43 0 24 Jun 2022
Hierarchical Distribution-Aware Testing of Deep Learning Wei Huang Xingyu Zhao Alec Banks V. Cox Xiaowei Huang OOD AAML 47 10 0 17 May 2022
Verifying Neural Networks Against Backdoor Attacks Long H. Pham Jun Sun AAML 26 5 0 14 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 26 48 0 01 May 2022
Software Testing for Machine Learning D. Marijan A. Gotlieb AAML 24 27 0 30 Apr 2022
Reachability In Simple Neural Networks Marco Sälzer M. Lange 30 1 0 15 Mar 2022
Verification-Aided Deep Ensemble Selection Guy Amir Tom Zelazny Guy Katz Michael Schapira AAML 30 18 0 08 Feb 2022
Systems Challenges for Trustworthy Embodied Systems Harald Ruess 21 2 0 10 Jan 2022
Curriculum Learning for Safe Mapless Navigation Luca Marzari Davide Corsi Enrico Marchesini Alessandro Farinelli 30 14 0 23 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 28 13 0 14 Dec 2021
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 31 65 0 15 Nov 2021
Sparse Adversarial Video Attacks with Spatial Transformations Ronghui Mu Wenjie Ruan Leandro Soriano Marcolino Q. Ni AAML 32 18 0 10 Nov 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 27 18 0 29 Oct 2021
Minimal Multi-Layer Modifications of Deep Neural Networks Idan Refaeli Guy Katz KELM AAML 35 15 0 18 Oct 2021
Reachability Is NP-Complete Even for the Simplest Neural Networks Marco Sälzer M. Lange 30 26 0 30 Aug 2021
Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe Panagiotis Vlantis Leila J. Bridgeman Michael M. Zavlanos 40 0 0 22 Jun 2021
The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning K. Morik Helena Kotthaus Lukas Heppe Danny Heinrich Raphael Fischer Andrea Pauly Nico Piatkowski 23 4 0 01 Jun 2021
DNNV: A Framework for Deep Neural Network Verification David Shriver Sebastian G. Elbaum Matthew B. Dwyer 21 31 0 26 May 2021
On Guaranteed Optimal Robust Explanations for NLP Models Emanuele La Malfa A. Zbrzezny Rhiannon Michelmore Nicola Paoletti Marta Z. Kwiatkowska FAtt 19 47 0 08 May 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 46 55 0 06 Apr 2021
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude Fu Lee Wang Yanghao Zhang Yanbin Zheng Wenjie Ruan 31 1 0 04 Mar 2021
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 39 48 0 19 Oct 2020
Assessing Robustness of Text Classification through Maximal Safe Radius Computation Emanuele La Malfa Min Wu Luca Laurenti Benjie Wang Anthony Hartshorn Marta Z. Kwiatkowska AAML 20 18 0 01 Oct 2020
Deep Learning & Software Engineering: State of Research and Future Directions P. Devanbu Matthew B. Dwyer Sebastian G. Elbaum M. Lowry Kevin Moran Denys Poshyvanyk Baishakhi Ray Rishabh Singh Xiangyu Zhang 11 22 0 17 Sep 2020
Adversarial Training and Provable Robustness: A Tale of Two Objectives Jiameng Fan Wenchao Li AAML 23 20 0 13 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 32 73 0 07 Aug 2020
Towards Visual Distortion in Black-Box Attacks Nannan Li Zhenzhong Chen 30 12 0 21 Jul 2020
Scaling Polyhedral Neural Network Verification on GPUs Christoph Müller F. Serre Gagandeep Singh Markus Püschel Martin Vechev AAML 29 56 0 20 Jul 2020
Abstraction based Output Range Analysis for Neural Networks P. Prabhakar Zahra Rahimi Afzal 38 62 0 18 Jul 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 37 437 0 17 Jun 2020
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs Christopher Brix T. Noll AAML 25 10 0 16 Jun 2020
Global Robustness Verification Networks Weidi Sun Yuteng Lu Xiyue Zhang Zhanxing Zhu Meng Sun AAML 22 2 0 08 Jun 2020
Probabilistic Guarantees for Safe Deep Reinforcement Learning E. Bacci David Parker 19 27 0 14 May 2020
Probabilistic Safety for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Marta Z. Kwiatkowska AAML 14 52 0 21 Apr 2020