Measuring Neural Net Robustness with Constraints

24 May 2016

Osbert Bastani

Yani Andrew Ioannou

Leonidas Lampropoulos

Papers citing "Measuring Neural Net Robustness with Constraints"

50 / 62 papers shown

Title
Verification of Neural Networks against Convolutional Perturbations via Parameterised Kernels Benedikt Brückner Alessio Lomuscio AAML 57 0 0 07 Nov 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers Jonas Ngnawé Sabyasachi Sahoo Y. Pequignot Frédéric Precioso Christian Gagné AAML 42 0 0 26 Jun 2024
A Survey of Neural Network Robustness Assessment in Image Recognition Jie Wang Jun Ai Minyan Lu Haoran Su Dan Yu Yutao Zhang Junda Zhu Jingyu Liu AAML 30 3 0 12 Apr 2024
Verifiable Boosted Tree Ensembles Stefano Calzavara Lorenzo Cazzaro Claudio Lucchese Giulio Ermanno Pibiri AAML 44 0 0 22 Feb 2024
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks Yang Wang B. Dong Ke Xu Haiyin Piao Yufei Ding Baocai Yin Xin Yang AAML 37 3 0 10 Oct 2023
gRoMA: a Tool for Measuring the Global Robustness of Deep Neural Networks Natan Levy Raz Yerushalmi Guy Katz AAML 25 1 0 05 Jan 2023
Efficiently Finding Adversarial Examples with DNN Preprocessing Avriti Chauhan Mohammad Afzal Hrishikesh Karmarkar Y. Elboher Kumar Madhukar Guy Katz AAML 26 0 0 16 Nov 2022
Adversarial Purification with the Manifold Hypothesis Zhaoyuan Yang Zhiwei Xu Jing Zhang Richard I. Hartley Peter Tu AAML 24 5 0 26 Oct 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
Understanding Adversarial Robustness of Vision Transformers via Cauchy Problem Zheng Wang Wenjie Ruan ViT 42 8 0 01 Aug 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 23 43 0 24 Jun 2022
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview Florian Karl Tobias Pielok Julia Moosbauer Florian Pfisterer Stefan Coors ... Jakob Richter Michel Lang Eduardo C. Garrido-Merchán Juergen Branke B. Bischl AI4CE 26 56 0 15 Jun 2022
Neural Network Verification with Proof Production Omri Isac Clark W. Barrett M. Zhang Guy Katz AAML 35 20 0 01 Jun 2022
CertiFair: A Framework for Certified Global Fairness of Neural Networks Haitham Khedr Yasser Shoukry FedML 26 19 0 20 May 2022
Software Testing for Machine Learning D. Marijan A. Gotlieb AAML 22 27 0 30 Apr 2022
An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks Matan Ostrovsky Clark W. Barrett Guy Katz 40 26 0 06 Jan 2022
Curriculum Learning for Safe Mapless Navigation Luca Marzari Davide Corsi Enrico Marchesini Alessandro Farinelli 22 14 0 23 Dec 2021
The Fundamental Limits of Interval Arithmetic for Neural Networks M. Mirman Maximilian Baader Martin Vechev 32 6 0 09 Dec 2021
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution Detection Nikolaos Dionelis Mehrdad Yaghoobi Sotirios A. Tsaftaris OODD 19 4 0 30 Nov 2021
Fast BATLLNN: Fast Box Analysis of Two-Level Lattice Neural Networks James Ferlez Haitham Khedr Yasser Shoukry 24 11 0 17 Nov 2021
RoMA: a Method for Neural Network Robustness Measurement and Assessment Natan Levy Guy Katz OOD AAML 10 13 0 21 Oct 2021
Lyapunov-stable neural-network control Hongkai Dai Benoit Landry Lujie Yang Marco Pavone Russ Tedrake 15 119 0 29 Sep 2021
DNNV: A Framework for Deep Neural Network Verification David Shriver Sebastian G. Elbaum Matthew B. Dwyer 21 31 0 26 May 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 39 55 0 06 Apr 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Muhammad Shafique Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 78 100 0 04 Jan 2021
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 24 84 0 12 Nov 2020
An SMT-Based Approach for Verifying Binarized Neural Networks Guy Amir Haoze Wu Clark W. Barrett Guy Katz 19 58 0 05 Nov 2020
Transferable Universal Adversarial Perturbations Using Generative Models Atiyeh Hashemi Andreas Bär S. Mozaffari Tim Fingscheidt AAML 22 17 0 28 Oct 2020
Safety Verification of Model Based Reinforcement Learning Controllers Akshita Gupta Inseok Hwang 37 5 0 21 Oct 2020
Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification Davide Corsi Enrico Marchesini Alessandro Farinelli OffRL 14 2 0 19 Oct 2020
Characterizing and Taming Model Instability Across Edge Devices Eyal Cidon Evgenya Pergament Zain Asgar Asaf Cidon Sachin Katti 14 7 0 18 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
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 38 62 0 11 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 25 73 0 07 Aug 2020
Robustifying Reinforcement Learning Agents via Action Space Adversarial Training Kai Liang Tan Yasaman Esfandiari Xian Yeow Lee Aakanksha S. Sarkar AAML 26 55 0 14 Jul 2020
ReluDiff: Differential Verification of Deep Neural Networks Brandon Paulsen Jingbo Wang Chao Wang 22 53 0 10 Jan 2020
An Abstraction-Based Framework for Neural Network Verification Y. Elboher Justin Emile Gottschlich Guy Katz 27 122 0 31 Oct 2019
Probabilistic Verification and Reachability Analysis of Neural Networks via Semidefinite Programming Mahyar Fazlyab M. Morari George J. Pappas AAML 35 41 0 09 Oct 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 43 474 0 03 Jul 2019
Machine Learning Testing: Survey, Landscapes and Horizons Jie M. Zhang Mark Harman Lei Ma Yang Liu VLM AILaw 21 739 0 19 Jun 2019
Testing DNN Image Classifiers for Confusion & Bias Errors Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail E. Kaiser Baishakhi Ray 24 52 0 20 May 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain Lei Bu Yuchao Duan Fu Song Zhe Zhao AAML 32 18 0 19 May 2019
How is Gaze Influenced by Image Transformations? Dataset and Model Zhaohui Che Ali Borji Guangtao Zhai Xiongkuo Min G. Guo P. Le Callet 27 76 0 16 May 2019
Algorithms for Verifying Deep Neural Networks Changliu Liu Tomer Arnon Christopher Lazarus Christopher A. Strong Clark W. Barrett Mykel J. Kochenderfer AAML 36 390 0 15 Mar 2019
Optimization Problems for Machine Learning: A Survey Claudio Gambella Bissan Ghaddar Joe Naoum-Sawaya AI4CE 30 178 0 16 Jan 2019
Evading classifiers in discrete domains with provable optimality guarantees B. Kulynych Jamie Hayes N. Samarin Carmela Troncoso AAML 15 19 0 25 Oct 2018
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm Tsui-Wei Weng Huan Zhang Pin-Yu Chen A. Lozano Cho-Jui Hsieh Luca Daniel 25 10 0 19 Oct 2018
Empirical Bounds on Linear Regions of Deep Rectifier Networks Thiago Serra Srikumar Ramalingam 8 42 0 08 Oct 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 50 226 0 18 Jul 2018
The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples Ayse Elvan Aydemir A. Temi̇zel T. Taşkaya-Temizel AAML 6 30 0 28 Mar 2018