Towards Stable and Efficient Training of Verifiably Robust Neural Networks

14 June 2019

Papers citing "Towards Stable and Efficient Training of Verifiably Robust Neural Networks"

22 / 22 papers shown

Title
Towards Universal Certified Robustness with Multi-Norm Training Enyi Jiang Gagandeep Singh Gagandeep Singh AAML 89 1 0 03 Oct 2024
On Using Certified Training towards Empirical Robustness Alessandro De Palma Serge Durand Zakaria Chihani François Terrier Caterina Urban OOD AAML 58 1 0 02 Oct 2024
CTBENCH: A Library and Benchmark for Certified Training Yuhao Mao Stefan Balauca Martin Vechev OOD 66 5 0 07 Jun 2024
Neural Network Verification with Branch-and-Bound for General Nonlinearities Zhouxing Shi Qirui Jin Zico Kolter Suman Jana Cho-Jui Hsieh Huan Zhang 64 14 0 31 May 2024
Probabilistic Verification of Neural Networks using Branch and Bound David Boetius Stefan Leue Tobias Sutter 66 1 0 27 May 2024
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples Antonio Emanuele Cinà Jérôme Rony Maura Pintor Christian Scano Ambra Demontis Battista Biggio Ismail Ben Ayed Fabio Roli ELM AAML SILM 75 9 0 30 Apr 2024
Specification Overfitting in Artificial Intelligence Benjamin Roth Pedro Henrique Luz de Araujo Yuxi Xia Saskia Kaltenbrunner Christoph Korab 129 1 0 13 Mar 2024
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing Devansh Bhardwaj Kshitiz Kaushik Sarthak Gupta AAML 53 0 0 12 Feb 2024
Is Adversarial Training with Compressed Datasets Effective? Tong Chen Raghavendra Selvan AAML 105 0 0 08 Feb 2024
Set-Based Training for Neural Network Verification Lukas Koller Tobias Ladner Matthias Althoff AAML 67 2 0 26 Jan 2024
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 117 36 0 29 Apr 2023
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 99 2,018 0 08 Feb 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 51 145 0 15 Jan 2019
Verification of deep probabilistic models Krishnamurthy Dvijotham M. Garnelo Alhussein Fawzi Pushmeet Kohli 34 23 0 06 Dec 2018
Distributionally Adversarial Attack T. Zheng Changyou Chen K. Ren OOD 72 121 0 16 Aug 2018
Structured Adversarial Attack: Towards General Implementation and Better Interpretability Kaidi Xu Sijia Liu Pu Zhao Pin-Yu Chen Huan Zhang Quanfu Fan Deniz Erdogmus Yanzhi Wang Xinyu Lin AAML 87 160 0 05 Aug 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 67 1,172 0 17 May 2018
Towards Fast Computation of Certified Robustness for ReLU Networks Tsui-Wei Weng Huan Zhang Hongge Chen Zhao Song Cho-Jui Hsieh Duane S. Boning Inderjit S. Dhillon Luca Daniel AAML 76 689 0 25 Apr 2018
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong Warren He James Wei Xinyun Chen Nicholas Carlini D. Song AAML 66 242 0 15 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 103 1,851 0 20 May 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 290 1,849 0 03 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 448 3,124 0 04 Nov 2016