Efficient Formal Safety Analysis of Neural Networks

Efficient Formal Safety Analysis of Neural Networks

19 September 2018

Justin Whitehouse

Papers citing "Efficient Formal Safety Analysis of Neural Networks"

17 / 17 papers shown

Title
Data-Driven Falsification of Cyber-Physical Systems Atanu Kundu Sauvik Gon Rajarshi Ray AAML AI4CE 48 3 0 06 May 2025
Evaluation and Verification of Physics-Informed Neural Models of the Grad-Shafranov Equation Fauzan Nazranda Rizqan Matthew Hole Charles Gretton 63 0 0 29 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 117 1 0 12 Dec 2024
Verification of Neural Networks against Convolutional Perturbations via Parameterised Kernels Benedikt Brückner Alessio Lomuscio AAML 61 1 0 07 Nov 2024
Revisiting Differential Verification: Equivalence Verification with Confidence Samuel Teuber Philipp Kern Marvin Janzen Bernhard Beckert 54 0 0 26 Oct 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 57 1 0 27 May 2024
Towards Certification of Uncertainty Calibration under Adversarial Attacks Cornelius Emde Francesco Pinto Thomas Lukasiewicz Philip Torr Adel Bibi AAML 66 0 0 22 May 2024
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 117 36 0 29 Apr 2023
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification Brendon G. Anderson Ziye Ma Jingqi Li Somayeh Sojoudi 73 1 0 22 Jan 2021
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 72 688 0 25 Apr 2018
Towards Proving the Adversarial Robustness of Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel J. Kochenderfer AAML OOD 29 118 0 08 Sep 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 85 3,848 0 10 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 134 2,854 0 14 Mar 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 288 1,849 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 198 935 0 21 Oct 2016
On the number of response regions of deep feed forward networks with piece-wise linear activations Razvan Pascanu Guido Montúfar Yoshua Bengio FAtt 88 257 0 20 Dec 2013