Probabilistic Safety for Bayesian Neural Networks

Probabilistic Safety for Bayesian Neural Networks

21 April 2020

Marta Z. Kwiatkowska

Papers citing "Probabilistic Safety for Bayesian Neural Networks"

14 / 14 papers shown

Title
Support is All You Need for Certified VAE Training Changming Xu Debangshu Banerjee Deepak Vasisht Gagandeep Singh AAML 39 0 0 16 Apr 2025
Certified Guidance for Planning with Deep Generative Models Francesco Giacomarra Mehran Hosseini Nicola Paoletti Francesca Cairoli 43 0 0 22 Jan 2025
Probabilistic Verification of Neural Networks using Branch and Bound David Boetius Stefan Leue Tobias Sutter 42 0 0 27 May 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
When to Trust AI: Advances and Challenges for Certification of Neural Networks M. Kwiatkowska Xiyue Zhang AAML 12 8 0 20 Sep 2023
Distributionally Robust Statistical Verification with Imprecise Neural Networks Souradeep Dutta Michele Caprio Vivian Lin Matthew Cleaveland Kuk Jin Jang I. Ruchkin O. Sokolsky Insup Lee OOD AAML 49 7 0 28 Aug 2023
Provable Preimage Under-Approximation for Neural Networks (Full Version) Xiyue Zhang Benjie Wang Marta Z. Kwiatkowska AAML 34 7 0 05 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples Qizhang Li Yiwen Guo W. Zuo Hao Chen AAML 27 35 0 10 Feb 2023
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 21 17 0 16 Dec 2022
Individual Fairness Guarantees for Neural Networks Elias Benussi A. Patané Matthew Wicker Luca Laurenti Marta Kwiatkowska University of Oxford 20 21 0 11 May 2022
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications Leonard Berrada Sumanth Dathathri Krishnamurthy Dvijotham Robert Stanforth Rudy Bunel J. Uesato Sven Gowal M. P. Kumar AAML OOD 30 17 0 18 Feb 2021
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 228 1,835 0 03 Feb 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015