Adversarial Ink: Componentwise Backward Error Attacks on Deep Learning

5 June 2023

Papers citing "Adversarial Ink: Componentwise Backward Error Attacks on Deep Learning"

8 / 8 papers shown

Title
Numerical Error Analysis of Large Language Models Stanislav Budzinskiy Wenyi Fang Longbin Zeng Philipp Petersen 47 1 0 13 Mar 2025
Low-Rank Adversarial PGD Attack Dayana Savostianova Emanuele Zangrando Francesco Tudisco AAML 23 0 0 16 Oct 2024
Deceptive Diffusion: Generating Synthetic Adversarial Examples Lucas Beerens Catherine F. Higham D. Higham WIGM DiffM 28 2 0 28 Jun 2024
Preconditioning for Physics-Informed Neural Networks Songming Liu Chang Su J. Yao Zhongkai Hao Hang Su Youjia Wu Jun Zhu AI4CE PINN 41 5 0 01 Feb 2024
Do stable neural networks exist for classification problems? -- A new view on stability in AI Z. N. D. Liu A. C. Hansen 22 0 0 15 Jan 2024
Vulnerability Analysis of Transformer-based Optical Character Recognition to Adversarial Attacks Lucas Beerens D. Higham 36 1 0 28 Nov 2023
Can We Rely on AI? D. Higham AAML 35 0 0 29 Aug 2023
The Feasibility and Inevitability of Stealth Attacks I. Tyukin D. Higham Alexander Bastounis Eliyas Woldegeorgis Alexander N. Gorban AAML 14 19 0 26 Jun 2021