Make Sure You're Unsure: A Framework for Verifying Probabilistic
Specifications

Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications

18 February 2021

Leonard Berrada

Sumanth Dathathri

Krishnamurthy Dvijotham

Robert Stanforth

Papers citing "Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications"

16 / 16 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
Probabilistic Verification of Neural Networks using Branch and Bound David Boetius Stefan Leue Tobias Sutter 39 0 0 27 May 2024
Out-of-Distribution Data: An Acquaintance of Adversarial Examples -- A Survey Naveen Karunanayake Ravin Gunawardena Suranga Seneviratne Sanjay Chawla OOD 38 5 0 08 Apr 2024
Tight Verification of Probabilistic Robustness in Bayesian Neural Networks Ben Batten Mehran Hosseini A. Lomuscio AAML 11 5 0 21 Jan 2024
Probabilistic Reach-Avoid for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Nicola Paoletti Alessandro Abate Marta Z. Kwiatkowska 16 2 0 03 Oct 2023
Adversarial Robustness Certification for Bayesian Neural Networks Matthew Wicker A. Patané Luca Laurenti Marta Z. Kwiatkowska AAML 23 3 0 23 Jun 2023
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming Steven Adams A. Patané Morteza Lahijanian Luca Laurenti AAML 82 7 0 19 Jun 2023
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection Nicola Franco Daniel Korth J. Lorenz Karsten Roscher Stephan Guennemann 26 5 0 27 Mar 2023
Provably Bounding Neural Network Preimages Suhas Kotha Christopher Brix Zico Kolter Krishnamurthy Dvijotham Huan Zhang AAML 30 12 0 02 Feb 2023
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 19 17 0 16 Dec 2022
Probabilistic Verification of ReLU Neural Networks via Characteristic Functions Joshua Pilipovsky Vignesh Sivaramakrishnan Meeko Oishi Panagiotis Tsiotras 27 4 0 03 Dec 2022
On the Robustness of Bayesian Neural Networks to Adversarial Attacks Luca Bortolussi Ginevra Carbone Luca Laurenti A. Patané G. Sanguinetti Matthew Wicker AAML 16 11 0 13 Jul 2022
Specifying and Testing $k$ -Safety Properties for Machine-Learning Models M. Christakis Hasan Ferit Eniser Jörg Hoffmann Adish Singla Valentin Wüstholz 11 5 0 13 Jun 2022
Provably Robust Detection of Out-of-distribution Data (almost) for free Alexander Meinke Julian Bitterwolf Matthias Hein OODD 12 22 0 08 Jun 2021
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 224 1,835 0 03 Feb 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,134 0 06 Jun 2015