The Fundamental Limits of Interval Arithmetic for Neural Networks

The Fundamental Limits of Interval Arithmetic for Neural Networks

9 December 2021

Maximilian Baader

Martin Vechev

Papers citing "The Fundamental Limits of Interval Arithmetic for Neural Networks"

8 / 8 papers shown

Title
Certified Robust Accuracy of Neural Networks Are Bounded due to Bayes Errors Ruihan Zhang Jun Sun AAML 34 3 0 19 May 2024
Quantization-aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks Mathias Lechner Dorde Zikelic K. Chatterjee T. Henzinger Daniela Rus AAML 16 2 0 29 Nov 2022
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective Bohang Zhang Du Jiang Di He Liwei Wang OOD 36 47 0 04 Oct 2022
Spelunking the Deep: Guaranteed Queries on General Neural Implicit Surfaces via Range Analysis Nicholas Sharp Alec Jacobson 34 26 0 05 Feb 2022
Boosting the Certified Robustness of L-infinity Distance Nets Bohang Zhang Du Jiang Di He Liwei Wang OOD 32 29 0 13 Oct 2021
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 108 138 0 29 Nov 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 231 1,837 0 03 Feb 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016